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Tutorial
Sat Aug 05 03:45 PM -- 06:00 PM (PDT) @ Cockle Bay
Distributed Deep Learning with MxNet Gluon
Tutorial
Sat Aug 05 03:45 PM -- 06:00 PM (PDT) @ Parkside 1
Interpretable Machine Learning
Tutorial
Sat Aug 05 03:45 PM -- 06:00 PM (PDT) @ Parkside 2
Machine Learning for Autonomous Vehicles
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Video]
Tutorial
Sat Aug 05 08:00 PM -- 10:15 PM (PDT) @ Cockle Bay
Recent Advances in Stochastic Convex and Non-Convex Optimization
Tutorial
Sat Aug 05 08:00 PM -- 10:15 PM (PDT) @ Parkside 1
Deep Reinforcement Learning, Decision Making, and Control
Tutorial
Sat Aug 05 08:00 PM -- 10:15 PM (PDT) @ Parkside 2
Deep Learning for Health Care Applications: Challenges and Solutions
Tutorial
Sat Aug 05 10:45 PM -- 01:00 AM (PDT) @ Cockle Bay
Real World Interactive Learning
Tutorial
Sat Aug 05 10:45 PM -- 01:00 AM (PDT) @ Parkside 1
Sequence-To-Sequence Modeling with Neural Networks
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Video]
Tutorial
Sat Aug 05 10:45 PM -- 01:00 AM (PDT) @ Parkside 2
Robustness Meets Algorithms (and Vice-Versa)
Break
Sun Aug 06 07:00 AM -- 06:00 PM (PDT) @ Ground Level
Registration Desk
Break
Sun Aug 06 08:15 AM -- 08:45 AM (PDT) @ Gallery
Coffee Break
Break
Sun Aug 06 11:00 AM -- 01:00 PM (PDT) @ On your own
Lunch - on your own
Break
Sun Aug 06 11:00 AM -- 11:30 AM (PDT) @ Gallery
Coffee Break
Break
Sun Aug 06 03:15 PM -- 03:45 PM (PDT) @ Gallery
Coffee Break
Invited Talk
Sun Aug 06 04:00 PM -- 05:00 PM (PDT) @ Darling Harbour Theatre
Causal Learning
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Video]
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ Darling Harbour Theatre
Decoupled Neural Interfaces using Synthetic Gradients
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PDF]
[
Summary/Notes]
Summary/Notes]
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ Parkside 1
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ Parkside 2
Tight Bounds for Approximate Carathéodory and Beyond
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.5
Robust Adversarial Reinforcement Learning
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.9& C4.10
Robust Probabilistic Modeling with Bayesian Data Reweighting
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.1
Multi-objective Bandits: Optimizing the Generalized Gini Index
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.4
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.8
The loss surface of deep and wide neural networks
Talk
Sun Aug 06 05:30 PM -- 05:48 PM (PDT) @ C4.6 & C4.7
Enumerating Distinct Decision Trees
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ Darling Harbour Theatre
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ Parkside 1
Parallel Multiscale Autoregressive Density Estimation
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ Parkside 2
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.5
Minimax Regret Bounds for Reinforcement Learning
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.9& C4.10
Post-Inference Prior Swapping
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.1
Online Learning with Local Permutations and Delayed Feedback
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.4
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.8
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
Talk
Sun Aug 06 05:48 PM -- 06:06 PM (PDT) @ C4.6 & C4.7
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ Darling Harbour Theatre
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ Parkside 1
Video Pixel Networks
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PDF]
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Summary/Notes]
Summary/Notes]
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ Parkside 2
Global optimization of Lipschitz functions
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.5
Fairness in Reinforcement Learning
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.9& C4.10
Evaluating Bayesian Models with Posterior Dispersion Indices
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.1
Model-Independent Online Learning for Influence Maximization
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.4
Latent Feature Lasso
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.8
Sharp Minima Can Generalize For Deep Nets
Talk
Sun Aug 06 06:06 PM -- 06:24 PM (PDT) @ C4.6 & C4.7
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
Break
Sun Aug 06 06:15 PM -- 07:15 PM (PDT) @ Ballroom
Opening Reception
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ Darling Harbour Theatre
Learning Important Features Through Propagating Activation Differences
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ Parkside 1
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ Parkside 2
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.5
Boosted Fitted Q-Iteration
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.9& C4.10
Automatic Discovery of the Statistical Types of Variables in a Dataset
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.1
Online Learning to Rank in Stochastic Click Models
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.4
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.8
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Talk
Sun Aug 06 06:24 PM -- 06:42 PM (PDT) @ C4.6 & C4.7
Multi-Class Optimal Margin Distribution Machine
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ Darling Harbour Theatre
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ Parkside 1
Learning Texture Manifolds with the Periodic Spatial GAN
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ Parkside 2
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ C4.5
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ C4.9& C4.10
Bayesian Models of Data Streams with Hierarchical Power Priors
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ C4.1
The Sample Complexity of Online One-Class Collaborative Filtering
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ C4.8
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
Talk
Sun Aug 06 06:42 PM -- 07:00 PM (PDT) @ C4.6 & C4.7
Kernelized Support Tensor Machines
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ Darling Harbour Theatre
Equivariance Through Parameter-Sharing
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ Parkside 1
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ Parkside 2
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.5
Constrained Policy Optimization
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.9& C4.10
Ordinal Graphical Models: A Tale of Two Approaches
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.1
Efficient Regret Minimization in Non-Convex Games
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.4
Coresets for Vector Summarization with Applications to Network Graphs
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.8
Recovery Guarantees for One-hidden-layer Neural Networks
Talk
Sun Aug 06 08:30 PM -- 08:48 PM (PDT) @ C4.6 & C4.7
Dual Supervised Learning
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ Darling Harbour Theatre
Warped Convolutions: Efficient Invariance to Spatial Transformations
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ Parkside 1
McGan: Mean and Covariance Feature Matching GAN
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ Parkside 2
Breaking Locality Accelerates Block Gauss-Seidel
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.5
Reinforcement Learning with Deep Energy-Based Policies
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.9& C4.10
Scalable Bayesian Rule Lists
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.1
Identify the Nash Equilibrium in Static Games with Random Payoffs
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.4
Partitioned Tensor Factorizations for Learning Mixed Membership Models
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.8
Failures of Gradient-Based Deep Learning
Talk
Sun Aug 06 08:48 PM -- 09:06 PM (PDT) @ C4.6 & C4.7
Learning Infinite Layer Networks without the Kernel Trick
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ Darling Harbour Theatre
Graph-based Isometry Invariant Representation Learning
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ Parkside 1
Conditional Image Synthesis with Auxiliary Classifier GANs
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ Parkside 2
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.5
Prediction and Control with Temporal Segment Models
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.9& C4.10
Learning Determinantal Point Processes with Moments and Cycles
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.1
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.4
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.8
Analytical Guarantees on Numerical Precision of Deep Neural Networks
Talk
Sun Aug 06 09:06 PM -- 09:24 PM (PDT) @ C4.6 & C4.7
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ Darling Harbour Theatre
Deriving Neural Architectures from Sequence and Graph Kernels
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ Parkside 1
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ Parkside 2
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.5
An Alternative Softmax Operator for Reinforcement Learning
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.9& C4.10
Deep Bayesian Active Learning with Image Data
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.1
On Kernelized Multi-armed Bandits
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.4
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.8
Follow the Moving Leader in Deep Learning
Talk
Sun Aug 06 09:24 PM -- 09:42 PM (PDT) @ C4.6 & C4.7
Logarithmic Time One-Against-Some
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ Darling Harbour Theatre
Unsupervised Learning by Predicting Noise
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Summary/Notes]
Summary/Notes]
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ Parkside 1
Wasserstein Generative Adversarial Networks
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ Parkside 2
Connected Subgraph Detection with Mirror Descent on SDPs
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.5
Fake News Mitigation via Point Process Based Intervention
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.9& C4.10
Bayesian Boolean Matrix Factorisation
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.1
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.4
Frame-based Data Factorizations
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.8
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Talk
Sun Aug 06 09:42 PM -- 10:00 PM (PDT) @ C4.6 & C4.7
Understanding Black-box Predictions via Influence Functions
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ Darling Harbour Theatre
Deep Transfer Learning with Joint Adaptation Networks
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ Parkside 1
Learning Hierarchical Features from Deep Generative Models
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ Parkside 2
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.5
Curiosity-driven Exploration by Self-supervised Prediction
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.9& C4.10
Learning the Structure of Generative Models without Labeled Data
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.1
Dueling Bandits with Weak Regret
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.4
Nearly Optimal Robust Matrix Completion
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.8
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Talk
Sun Aug 06 10:30 PM -- 10:48 PM (PDT) @ C4.6 & C4.7
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ Darling Harbour Theatre
Meta Networks
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ Parkside 1
Bottleneck Conditional Density Estimation
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ Parkside 2
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.5
Interactive Learning from Policy-Dependent Human Feedback
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.9& C4.10
Learning to Discover Sparse Graphical Models
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.1
On Context-Dependent Clustering of Bandits
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.4
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.8
Convexified Convolutional Neural Networks
Talk
Sun Aug 06 10:48 PM -- 11:06 PM (PDT) @ C4.6 & C4.7
Self-Paced Co-training
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ Darling Harbour Theatre
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ Parkside 1
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ Parkside 2
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.5
End-to-End Differentiable Adversarial Imitation Learning
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.9& C4.10
Local-to-Global Bayesian Network Structure Learning
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.1
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.4
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.8
On the Expressive Power of Deep Neural Networks
Talk
Sun Aug 06 11:06 PM -- 11:24 PM (PDT) @ C4.6 & C4.7
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ Darling Harbour Theatre
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ Parkside 1
Zero-Inflated Exponential Family Embeddings
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ Parkside 2
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.5
Learning in POMDPs with Monte Carlo Tree Search
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.9& C4.10
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.1
Safety-Aware Algorithms for Adversarial Contextual Bandit
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.4
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.8
Depth-Width Tradeoffs in Approximating Natural Functions With Neural Networks
Talk
Sun Aug 06 11:24 PM -- 11:42 PM (PDT) @ C4.6 & C4.7
Iterative Machine Teaching
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ Darling Harbour Theatre
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ Parkside 2
Convex Phase Retrieval without Lifting via PhaseMax
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ C4.5
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ C4.9& C4.10
On Relaxing Determinism in Arithmetic Circuits
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ C4.1
Adaptive Multiple-Arm Identification
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ C4.4
Tensor Decomposition with Smoothness
Talk
Sun Aug 06 11:42 PM -- 12:00 AM (PDT) @ C4.6 & C4.7
Automated Curriculum Learning for Neural Networks
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ Darling Harbour Theatre
Learning to Learn without Gradient Descent by Gradient Descent
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ Parkside 1
Attentive Recurrent Comparators
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ Parkside 2
A Semismooth Newton Method for Fast, Generic Convex Programming
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.5
Unifying task specification in reinforcement learning
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.9& C4.10
An Infinite Hidden Markov Model With Similarity-Biased Transitions
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.1
Efficient Online Bandit Multiclass Learning with O(sqrt{T}) Regret
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.4
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.8
Efficient Nonmyopic Active Search
Talk
Mon Aug 07 12:15 AM -- 12:33 AM (PDT) @ C4.6 & C4.7
Asymmetric Tri-training for Unsupervised Domain Adaptation
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ Darling Harbour Theatre
Learned Optimizers that Scale and Generalize
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ Parkside 1
State-Frequency Memory Recurrent Neural Networks
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ Parkside 2
Approximate Newton Methods and Their Local Convergence
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.5
A Distributional Perspective on Reinforcement Learning
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.9& C4.10
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.1
Active Learning for Accurate Estimation of Linear Models
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.4
Tensor Decomposition via Simultaneous Power Iteration
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.8
Leveraging Union of Subspace Structure to Improve Constrained Clustering
Talk
Mon Aug 07 12:33 AM -- 12:51 AM (PDT) @ C4.6 & C4.7
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ Darling Harbour Theatre
Learning Gradient Descent: Better Generalization and Longer Horizons
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ Parkside 1
Delta Networks for Optimized Recurrent Network Computation
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ Parkside 2
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.5
Hierarchy Through Composition with Multitask LMDPs
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.9& C4.10
From Patches to Images: A Nonparametric Generative Model
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.1
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.4
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.8
Active Heteroscedastic Regression
Talk
Mon Aug 07 12:51 AM -- 01:09 AM (PDT) @ C4.6 & C4.7
Multi-task Learning with Labeled and Unlabeled Tasks
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ Darling Harbour Theatre
Learning Algorithms for Active Learning
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ Parkside 1
Recurrent Highway Networks
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ Parkside 2
Practical Gauss-Newton Optimisation for Deep Learning
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.5
A Laplacian Framework for Option Discovery in Reinforcement Learning
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.9& C4.10
Fast Bayesian Intensity Estimation for the Permanental Process
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.1
Emulating the Expert: Inverse Optimization through Online Learning
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.4
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.8
Active Learning for Cost-Sensitive Classification
Talk
Mon Aug 07 01:09 AM -- 01:27 AM (PDT) @ C4.6 & C4.7
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ Parkside 2
Tensor Balancing on Statistical Manifold
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.5
Modular Multitask Reinforcement Learning with Policy Sketches
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.9& C4.10
A Birth-Death Process for Feature Allocation
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.1
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.4
Algorithms for $\ell_p$ Low-Rank Approximation
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.8
Diameter-Based Active Learning
Talk
Mon Aug 07 01:27 AM -- 01:45 AM (PDT) @ C4.6 & C4.7
Risk Bounds for Transferring Representations With and Without Fine-Tuning
Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #1
Decoupled Neural Interfaces using Synthetic Gradients
In
Posters Mon
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #2
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
In
Posters Mon
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #3
Tight Bounds for Approximate Carathéodory and Beyond
In
Posters Mon
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Summary/Notes]
Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #4
Robust Adversarial Reinforcement Learning
In
Posters Mon
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #5
Robust Probabilistic Modeling with Bayesian Data Reweighting
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #6
Multi-objective Bandits: Optimizing the Generalized Gini Index
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #7
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #8
Enumerating Distinct Decision Trees
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #9
Understanding Synthetic Gradients and Decoupled Neural Interfaces
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #10
Parallel Multiscale Autoregressive Density Estimation
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #11
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #12
Minimax Regret Bounds for Reinforcement Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #13
Post-Inference Prior Swapping
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #14
Online Learning with Local Permutations and Delayed Feedback
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #15
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #16
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #17
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #18
Video Pixel Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #19
Global optimization of Lipschitz functions
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #20
Fairness in Reinforcement Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #21
Evaluating Bayesian Models with Posterior Dispersion Indices
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #22
Model-Independent Online Learning for Influence Maximization
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #23
Latent Feature Lasso
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #24
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #25
Learning Important Features Through Propagating Activation Differences
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #26
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #27
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #28
Boosted Fitted Q-Iteration
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #29
Automatic Discovery of the Statistical Types of Variables in a Dataset
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #30
Online Learning to Rank in Stochastic Click Models
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #31
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #32
Multi-Class Optimal Margin Distribution Machine
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #33
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #34
Learning Texture Manifolds with the Periodic Spatial GAN
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #35
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #36
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #37
Bayesian Models of Data Streams with Hierarchical Power Priors
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #38
The Sample Complexity of Online One-Class Collaborative Filtering
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #39
Kernelized Support Tensor Machines
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #40
Equivariance Through Parameter-Sharing
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #41
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #42
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #43
Constrained Policy Optimization
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #44
Ordinal Graphical Models: A Tale of Two Approaches
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #45
Efficient Regret Minimization in Non-Convex Games
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #46
Coresets for Vector Summarization with Applications to Network Graphs
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #47
Recovery Guarantees for One-hidden-layer Neural Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #48
Dual Supervised Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #49
Warped Convolutions: Efficient Invariance to Spatial Transformations
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #50
McGan: Mean and Covariance Feature Matching GAN
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #51
Breaking Locality Accelerates Block Gauss-Seidel
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #52
Reinforcement Learning with Deep Energy-Based Policies
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #53
Scalable Bayesian Rule Lists
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #54
Identify the Nash Equilibrium in Static Games with Random Payoffs
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #55
Partitioned Tensor Factorizations for Learning Mixed Membership Models
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #56
Failures of Gradient-Based Deep Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #57
Learning Infinite Layer Networks without the Kernel Trick
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #58
Graph-based Isometry Invariant Representation Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #59
Conditional Image Synthesis with Auxiliary Classifier GANs
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #60
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #61
Prediction and Control with Temporal Segment Models
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #62
Learning Determinantal Point Processes with Moments and Cycles
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #63
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #64
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #65
Analytical Guarantees on Numerical Precision of Deep Neural Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #66
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #67
Deriving Neural Architectures from Sequence and Graph Kernels
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #68
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #69
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #70
An Alternative Softmax Operator for Reinforcement Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #71
Deep Bayesian Active Learning with Image Data
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #72
On Kernelized Multi-armed Bandits
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #73
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #74
Follow the Moving Leader in Deep Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #75
Logarithmic Time One-Against-Some
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #76
Unsupervised Learning by Predicting Noise
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #77
Wasserstein Generative Adversarial Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #78
Connected Subgraph Detection with Mirror Descent on SDPs
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #79
Fake News Mitigation via Point Process Based Intervention
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #80
Bayesian Boolean Matrix Factorisation
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #81
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #82
Frame-based Data Factorizations
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #83
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #84
Understanding Black-box Predictions via Influence Functions
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #85
Deep Transfer Learning with Joint Adaptation Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #86
Learning Hierarchical Features from Deep Generative Models
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #87
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #88
Curiosity-driven Exploration by Self-supervised Prediction
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #89
Learning the Structure of Generative Models without Labeled Data
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #90
Dueling Bandits with Weak Regret
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #91
Nearly Optimal Robust Matrix Completion
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #92
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #93
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #94
Meta Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #95
Bottleneck Conditional Density Estimation
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #96
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #97
Interactive Learning from Policy-Dependent Human Feedback
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #98
Learning to Discover Sparse Graphical Models
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #99
On Context-Dependent Clustering of Bandits
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #100
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #101
Convexified Convolutional Neural Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #102
Self-Paced Co-training
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #103
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #104
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #105
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #106
End-to-End Differentiable Adversarial Imitation Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #107
Local-to-Global Bayesian Network Structure Learning
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #108
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #109
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #110
On the Expressive Power of Deep Neural Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #111
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #112
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #113
Zero-Inflated Exponential Family Embeddings
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #114
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #115
Learning in POMDPs with Monte Carlo Tree Search
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #116
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #117
Safety-Aware Algorithms for Adversarial Contextual Bandit
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #118
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #119
Depth-Width Tradeoffs in Approximating Natural Functions With Neural Networks
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #120
Iterative Machine Teaching
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #121
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #122
Convex Phase Retrieval without Lifting via PhaseMax
In
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #123
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
In
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #124
On Relaxing Determinism in Arithmetic Circuits
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #125
Adaptive Multiple-Arm Identification
In
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #126
Tensor Decomposition with Smoothness
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #127
Automated Curriculum Learning for Neural Networks
In
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #128
Attentive Recurrent Comparators
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #129
An Infinite Hidden Markov Model With Similarity-Biased Transitions
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #130
Efficient Nonmyopic Active Search
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #131
Asymmetric Tri-training for Unsupervised Domain Adaptation
In
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Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #132
State-Frequency Memory Recurrent Neural Networks
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #133
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #134
Leveraging Union of Subspace Structure to Improve Constrained Clustering
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #135
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #136
Delta Networks for Optimized Recurrent Network Computation
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #137
From Patches to Images: A Nonparametric Generative Model
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #138
Active Heteroscedastic Regression
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #139
Multi-task Learning with Labeled and Unlabeled Tasks
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #140
Recurrent Highway Networks
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #141
Fast Bayesian Intensity Estimation for the Permanental Process
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #142
Active Learning for Cost-Sensitive Classification
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #143
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #144
A Birth-Death Process for Feature Allocation
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #145
Diameter-Based Active Learning
In
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Poster
Mon Aug 07 01:30 AM -- 05:00 AM (PDT) @ Gallery #146
Risk Bounds for Transferring Representations With and Without Fine-Tuning
In
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Break
Mon Aug 07 07:00 AM -- 06:30 PM (PDT) @ Ground Level
Registration Desk
Break
Mon Aug 07 08:15 AM -- 08:45 AM (PDT) @ Gallery
Coffee Break
Break
Mon Aug 07 08:45 AM -- 09:00 AM (PDT) @ Darling Harbour Theatre
Opening Remarks
Break
Mon Aug 07 10:00 AM -- 10:30 AM (PDT) @ The Gallery
Coffee break
Break
Mon Aug 07 10:00 AM -- 11:00 AM (PDT) @ The Press Room at the ICC
Press Conference
Break
Mon Aug 07 12:00 PM -- 01:30 PM (PDT)
Lunch - on your own
Break
Mon Aug 07 03:00 PM -- 03:30 PM (PDT) @ The Gallery
Coffee Break
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ Darling Harbour Theatre
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ Parkside 1
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ Parkside 2
Lazifying Conditional Gradient Algorithms
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.5
Data-Efficient Policy Evaluation Through Behavior Policy Search
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.9& C4.10
Exact MAP Inference by Avoiding Fractional Vertices
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.1
Leveraging Node Attributes for Incomplete Relational Data
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.4
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.8
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Talk
Mon Aug 07 05:30 PM -- 05:48 PM (PDT) @ C4.6 & C4.7
Distributed and Provably Good Seedings for k-Means in Constant Rounds
In
Clustering 1
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ Darling Harbour Theatre
Learning Deep Architectures via Generalized Whitened Neural Networks
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ Parkside 1
On orthogonality and learning RNNs with long term dependencies
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ Parkside 2
Conditional Accelerated Lazy Stochastic Gradient Descent
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ C4.5
Stochastic Variance Reduction Methods for Policy Evaluation
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ C4.9& C4.10
Exact Inference for Integer Latent-Variable Models
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ C4.1
Bayesian inference on random simple graphs with power law degree distributions
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ C4.4
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Talk
Mon Aug 07 05:48 PM -- 06:06 PM (PDT) @ C4.8
Estimating the unseen from multiple populations
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ Darling Harbour Theatre
Continual Learning Through Synaptic Intelligence
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ Parkside 1
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ Parkside 2
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.5
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.9& C4.10
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.1
Analogical Inference for Multi-relational Embeddings
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.4
Spectral Learning from a Single Trajectory under Finite-State Policies
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.8
Meritocratic Fairness for Cross-Population Selection
Talk
Mon Aug 07 06:06 PM -- 06:24 PM (PDT) @ C4.6 & C4.7
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
In
Clustering 1
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ Darling Harbour Theatre
Adaptive Neural Networks for Efficient Inference
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ Parkside 1
The Statistical Recurrent Unit
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ Parkside 2
Approximate Steepest Coordinate Descent
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.5
Consistent On-Line Off-Policy Evaluation
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.9& C4.10
Variational Inference for Sparse and Undirected Models
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.1
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.4
Capacity Releasing Diffusion for Speed and Locality.
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.8
Neural networks and rational functions
Talk
Mon Aug 07 06:24 PM -- 06:42 PM (PDT) @ C4.6 & C4.7
Hyperplane Clustering Via Dual Principal Component Pursuit
In
Clustering 1
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ Darling Harbour Theatre
Combined Group and Exclusive Sparsity for Deep Neural Networks
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ Parkside 1
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ Parkside 2
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ C4.5
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ C4.9& C4.10
Tensor Belief Propagation
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ C4.1
Deep Generative Models for Relational Data with Side Information
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ C4.4
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Talk
Mon Aug 07 06:42 PM -- 07:00 PM (PDT) @ C4.6 & C4.7
Multilevel Clustering via Wasserstein Means
In
Clustering 1
Break
Mon Aug 07 06:45 PM -- 07:00 PM (PDT) @ Gallery
Light snack
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ Darling Harbour Theatre
Input Convex Neural Networks
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ Parkside 1
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ Parkside 2
Stochastic modified equations and adaptive stochastic gradient algorithms
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.5
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.9& C4.10
Faster Greedy MAP Inference for Determinantal Point Processes
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.1
ChoiceRank: Identifying Preferences from Node Traffic in Networks
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Summary/Notes]
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.4
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit
In
Sparsity 1
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.8
Uniform Deviation Bounds for k-Means Clustering
Talk
Mon Aug 07 08:30 PM -- 08:48 PM (PDT) @ C4.6 & C4.7
Co-clustering through Optimal Transport
In
Clustering 2
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ Darling Harbour Theatre
OptNet: Differentiable Optimization as a Layer in Neural Networks
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ Parkside 1
Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ Parkside 2
Dissipativity Theory for Nesterov's Accelerated Method
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.5
Gradient Boosted Decision Trees for High Dimensional Sparse Output
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.9& C4.10
Zonotope hit-and-run for efficient sampling from projection DPPs
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.1
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.4
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
In
Sparsity 1
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.8
Uniform Convergence Rates for Kernel Density Estimation
Talk
Mon Aug 07 08:48 PM -- 09:06 PM (PDT) @ C4.6 & C4.7
Multiple Clustering Views from Multiple Uncertain Experts
In
Clustering 2
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ Darling Harbour Theatre
Parseval Networks: Improving Robustness to Adversarial Examples
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ Parkside 1
Deep Voice: Real-time Neural Text-to-Speech
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ Parkside 2
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.5
Globally Induced Forest: A Prepruning Compression Scheme
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.9& C4.10
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
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Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.1
Just Sort It! A Simple and Effective Approach to Active Preference Learning
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.4
On The Projection Operator to A Three-view Cardinality Constrained Set
In
Sparsity 1
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.8
Density Level Set Estimation on Manifolds with DBSCAN
Talk
Mon Aug 07 09:06 PM -- 09:24 PM (PDT) @ C4.6 & C4.7
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
In
Clustering 2
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ Darling Harbour Theatre
Regularising Non-linear Models Using Feature Side-information
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ Parkside 1
DeepBach: a Steerable Model for Bach Chorales Generation
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ Parkside 2
Forward and Reverse Gradient-Based Hyperparameter Optimization
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.5
Forest-type Regression with General Losses and Robust Forest
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.9& C4.10
On the Sampling Problem for Kernel Quadrature
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.1
Maximum Selection and Ranking under Noisy Comparisons
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.4
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
In
Sparsity 1
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.8
Algorithmic Stability and Hypothesis Complexity
Talk
Mon Aug 07 09:24 PM -- 09:42 PM (PDT) @ C4.6 & C4.7
Clustering High Dimensional Dynamic Data Streams
In
Clustering 2
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ Parkside 1
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ Parkside 2
Adaptive Sampling Probabilities for Non-Smooth Optimization
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ C4.5
Confident Multiple Choice Learning
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ C4.9& C4.10
Measuring Sample Quality with Kernels
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ C4.1
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ C4.4
Compressed Sensing using Generative Models
In
Sparsity 1
Talk
Mon Aug 07 09:42 PM -- 10:00 PM (PDT) @ C4.8
Consistency Analysis for Binary Classification Revisited
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ Darling Harbour Theatre
A Closer Look at Memorization in Deep Networks
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ Parkside 1
Learning to Generate Long-term Future via Hierarchical Prediction
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ Parkside 2
Sub-sampled Cubic Regularization for Non-convex Optimization
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.5
Regret Minimization in Behaviorally-Constrained Zero-Sum Games
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.9& C4.10
Variational Boosting: Iteratively Refining Posterior Approximations
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.1
Learning to Align the Source Code to the Compiled Object Code
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.4
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
In
Sparsity 2
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.8
Distributed Mean Estimation with Limited Communication
Talk
Mon Aug 07 10:30 PM -- 10:48 PM (PDT) @ C4.6 & C4.7
Fast k-Nearest Neighbour Search via Prioritized DCI
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ Darling Harbour Theatre
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ Parkside 1
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ Parkside 2
Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.5
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.9& C4.10
Lost Relatives of the Gumbel Trick
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.1
RobustFill: Neural Program Learning under Noisy I/O
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.4
Efficient Distributed Learning with Sparsity
In
Sparsity 2
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.8
Nonparanormal Information Estimation
Talk
Mon Aug 07 10:48 PM -- 11:06 PM (PDT) @ C4.6 & C4.7
Deep Spectral Clustering Learning
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ Darling Harbour Theatre
Visualizing and Understanding Multilayer Perceptron Models: A Case Study in Speech Processing
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ Parkside 1
Tensor-Train Recurrent Neural Networks for Video Classification
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ Parkside 2
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.5
Strongly-Typed Agents are Guaranteed to Interact Safely
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.9& C4.10
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.1
Programming with a Differentiable Forth Interpreter
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.4
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
In
Sparsity 2
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.8
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions
Talk
Mon Aug 07 11:06 PM -- 11:24 PM (PDT) @ C4.6 & C4.7
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ Darling Harbour Theatre
Axiomatic Attribution for Deep Networks
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ Parkside 1
Sequence Modeling via Segmentations
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ Parkside 2
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.5
Coordinated Multi-Agent Imitation Learning
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.9& C4.10
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.1
Differentiable Programs with Neural Libraries
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.4
Selective Inference for Sparse High-Order Interaction Models
In
Sparsity 2
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.8
Gradient Coding: Avoiding Stragglers in Distributed Learning
Talk
Mon Aug 07 11:24 PM -- 11:42 PM (PDT) @ C4.6 & C4.7
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ Darling Harbour Theatre
On Calibration of Modern Neural Networks
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ Parkside 1
Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ Parkside 2
How to Escape Saddle Points Efficiently
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ C4.5
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ C4.9& C4.10
Learning Latent Space Models with Angular Constraints
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ C4.1
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ C4.4
Dictionary Learning Based on Sparse Distribution Tomography
In
Sparsity 2
Talk
Mon Aug 07 11:42 PM -- 12:00 AM (PDT) @ C4.8
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Invited Talk
Tue Aug 08 12:15 AM -- 01:15 AM (PDT) @ Darling Harbour Theatre
Genomics, Big Data, and Machine Learning: Understanding the Human Wiring Diagram and Driving the Healthcare Revolution
[
Video]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #1
The loss surface of deep and wide neural networks
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #2
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #3
Sharp Minima Can Generalize For Deep Nets
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #4
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #5
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #6
Learning to Learn without Gradient Descent by Gradient Descent
In
Posters Tue
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #7
A Semismooth Newton Method for Fast, Generic Convex Programming
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #8
Unifying task specification in reinforcement learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #9
Efficient Online Bandit Multiclass Learning with O(sqrt{T}) Regret
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #10
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #11
Learned Optimizers that Scale and Generalize
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #12
Approximate Newton Methods and Their Local Convergence
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #13
A Distributional Perspective on Reinforcement Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #14
Active Learning for Accurate Estimation of Linear Models
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #15
Tensor Decomposition via Simultaneous Power Iteration
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #16
Learning Gradient Descent: Better Generalization and Longer Horizons
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #17
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #18
Hierarchy Through Composition with Multitask LMDPs
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #19
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #20
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #21
Learning Algorithms for Active Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #22
Practical Gauss-Newton Optimisation for Deep Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #23
A Laplacian Framework for Option Discovery in Reinforcement Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #24
Emulating the Expert: Inverse Optimization through Online Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #25
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #26
Tensor Balancing on Statistical Manifold
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #27
Modular Multitask Reinforcement Learning with Policy Sketches
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #28
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #29
Algorithms for $\ell_p$ Low-Rank Approximation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #30
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #31
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #32
Lazifying Conditional Gradient Algorithms
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #33
Data-Efficient Policy Evaluation Through Behavior Policy Search
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #34
Exact MAP Inference by Avoiding Fractional Vertices
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #35
Leveraging Node Attributes for Incomplete Relational Data
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #36
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #37
Distributed and Provably Good Seedings for k-Means in Constant Rounds
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #38
Learning Deep Architectures via Generalized Whitened Neural Networks
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #39
On orthogonality and learning RNNs with long term dependencies
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #40
Conditional Accelerated Lazy Stochastic Gradient Descent
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #41
Stochastic Variance Reduction Methods for Policy Evaluation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #42
Exact Inference for Integer Latent-Variable Models
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #43
Bayesian inference on random simple graphs with power law degree distributions
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #44
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #45
Consistent k-Clustering
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #46
Continual Learning Through Synaptic Intelligence
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #47
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #48
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #49
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #50
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #51
Analogical Inference for Multi-relational Embeddings
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #52
Spectral Learning from a Single Trajectory under Finite-State Policies
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #53
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #54
Adaptive Neural Networks for Efficient Inference
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #55
The Statistical Recurrent Unit
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #56
Approximate Steepest Coordinate Descent
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #57
Consistent On-Line Off-Policy Evaluation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #58
Variational Inference for Sparse and Undirected Models
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #59
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #60
Capacity Releasing Diffusion for Speed and Locality.
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #61
Hyperplane Clustering Via Dual Principal Component Pursuit
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #62
Combined Group and Exclusive Sparsity for Deep Neural Networks
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #63
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #64
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #65
Contextual Decision Processes with low Bellman rank are PAC-Learnable
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #66
Tensor Belief Propagation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #67
Deep Generative Models for Relational Data with Side Information
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #68
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #69
Multilevel Clustering via Wasserstein Means
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #70
Online and Linear-Time Attention by Enforcing Monotonic Alignments
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #71
Stochastic modified equations and adaptive stochastic gradient algorithms
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #72
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #73
Faster Greedy MAP Inference for Determinantal Point Processes
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #74
ChoiceRank: Identifying Preferences from Node Traffic in Networks
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #75
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #76
Uniform Deviation Bounds for k-Means Clustering
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #77
Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #78
Dissipativity Theory for Nesterov's Accelerated Method
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #79
Gradient Boosted Decision Trees for High Dimensional Sparse Output
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #80
Zonotope hit-and-run for efficient sampling from projection DPPs
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #81
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #82
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #83
Uniform Convergence Rates for Kernel Density Estimation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #84
Deep Voice: Real-time Neural Text-to-Speech
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #85
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #86
Globally Induced Forest: A Prepruning Compression Scheme
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #87
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #88
Just Sort It! A Simple and Effective Approach to Active Preference Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #89
On The Projection Operator to A Three-view Cardinality Constrained Set
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #90
Density Level Set Estimation on Manifolds with DBSCAN
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #91
DeepBach: a Steerable Model for Bach Chorales Generation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #92
Forward and Reverse Gradient-Based Hyperparameter Optimization
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #93
Forest-type Regression with General Losses and Robust Forest
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #94
On the Sampling Problem for Kernel Quadrature
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #95
Maximum Selection and Ranking under Noisy Comparisons
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #96
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #97
Algorithmic Stability and Hypothesis Complexity
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #98
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #99
Adaptive Sampling Probabilities for Non-Smooth Optimization
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #100
Confident Multiple Choice Learning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #101
Measuring Sample Quality with Kernels
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #102
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #103
Compressed Sensing using Generative Models
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #104
Consistency Analysis for Binary Classification Revisited
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #105
A Closer Look at Memorization in Deep Networks
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #106
Learning to Generate Long-term Future via Hierarchical Prediction
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #107
Sub-sampled Cubic Regularization for Non-convex Optimization
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #108
Regret Minimization in Behaviorally-Constrained Zero-Sum Games
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #109
Variational Boosting: Iteratively Refining Posterior Approximations
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #110
Learning to Align the Source Code to the Compiled Object Code
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #111
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #112
Distributed Mean Estimation with Limited Communication
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #113
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #114
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #115
Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #116
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #117
Lost Relatives of the Gumbel Trick
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #118
RobustFill: Neural Program Learning under Noisy I/O
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #119
Efficient Distributed Learning with Sparsity
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #120
Nonparanormal Information Estimation
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #121
Visualizing and Understanding Multilayer Perceptron Models: A Case Study in Speech Processing
In
Posters Tue
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #122
Tensor-Train Recurrent Neural Networks for Video Classification
In
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #123
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
In
Posters Tue
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Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #124
Strongly-Typed Agents are Guaranteed to Interact Safely
In
Posters Tue
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Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #125
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
In
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Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #126
Programming with a Differentiable Forth Interpreter
In
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #127
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #128
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #129
Axiomatic Attribution for Deep Networks
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #130
Sequence Modeling via Segmentations
In
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #131
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #132
Coordinated Multi-Agent Imitation Learning
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #133
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #134
Differentiable Programs with Neural Libraries
In
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #135
Selective Inference for Sparse High-Order Interaction Models
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #136
Gradient Coding: Avoiding Stragglers in Distributed Learning
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #137
On Calibration of Modern Neural Networks
In
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Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #138
Latent LSTM Allocation: Joint clustering and non-linear dynamic modeling of sequence data
In
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #139
How to Escape Saddle Points Efficiently
In
Posters Tue
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #140
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
In
Posters Tue
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Summary/Notes]
Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #141
Learning Latent Space Models with Angular Constraints
In
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #142
Developing Bug-Free Machine Learning Systems With Formal Mathematics
In
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #143
Dictionary Learning Based on Sparse Distribution Tomography
In
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Summary/Notes]
Poster
Tue Aug 08 01:30 AM -- 05:00 AM (PDT) @ Gallery #144
Learning Discrete Representations via Information Maximizing Self-Augmented Training
In
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Summary/Notes]
Summary/Notes]
Break
Tue Aug 08 07:00 AM -- 06:00 PM (PDT) @ Ground Level
Registration Desk
Break
Tue Aug 08 08:15 AM -- 09:00 AM (PDT) @ Gallery
Coffee Break
Break
Tue Aug 08 10:00 AM -- 10:30 AM (PDT) @ The Gallery
Coffee Break
Break
Tue Aug 08 12:00 PM -- 01:30 PM (PDT)
Lunch on your own
Break
Tue Aug 08 03:00 PM -- 03:30 PM (PDT) @ The Gallery
Coffee Break
Invited Talk
Tue Aug 08 04:00 PM -- 05:45 PM (PDT) @ Darling Harbour Theatre
Towards Reinforcement Learning in the Real World
[
Video]
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ Darling Harbour Theatre
Device Placement Optimization with Reinforcement Learning
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ Parkside 2
Asynchronous Stochastic Gradient Descent with Delay Compensation
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.5
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.9& C4.10
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.1
Preferential Bayesian Optmization
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.4
Being Robust (in High Dimensions) Can Be Practical
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.8
Differentially Private Ordinary Least Squares
Talk
Tue Aug 08 05:30 PM -- 05:48 PM (PDT) @ C4.6 & C4.7
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
In
Healthcare
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ Darling Harbour Theatre
Deep Tensor Convolution on Multicores
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ Parkside 1
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
In
Language 1
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ Parkside 2
Adaptive Consensus ADMM for Distributed Optimization
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.5
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.9& C4.10
Stochastic Bouncy Particle Sampler
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.1
Max-value Entropy Search for Efficient Bayesian Optimization
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.4
Multilabel Classification with Group Testing and Codes
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.8
Priv’IT: Private and Sample Efficient Identity Testing
Talk
Tue Aug 08 05:48 PM -- 06:06 PM (PDT) @ C4.6 & C4.7
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
In
Healthcare
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ Darling Harbour Theatre
MEC: Memory-efficient Convolution for Deep Neural Network
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ Parkside 1
Coupling Distributed and Symbolic Execution for Natural Language Queries
In
Language 1
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ Parkside 2
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.5
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.9& C4.10
Canopy --- Fast Sampling with Cover Trees
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.1
Bayesian Optimization with Tree-structured Dependencies
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.4
High-Dimensional Structured Quantile Regression
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.8
Differentially Private Submodular Maximization: Data Summarization in Disguise
Talk
Tue Aug 08 06:06 PM -- 06:24 PM (PDT) @ C4.6 & C4.7
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
In
Healthcare
Break
Tue Aug 08 06:15 PM -- 07:00 PM (PDT) @ Gallery
Light snack
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ Darling Harbour Theatre
Beyond Filters: Compact Feature Map for Portable Deep Model
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ Parkside 1
Image-to-Markup Generation with Coarse-to-Fine Attention
In
Language 1
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ Parkside 2
Projection-free Distributed Online Learning in Networks
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.5
Learning Stable Stochastic Nonlinear Dynamical Systems
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.9& C4.10
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.1
Multi-fidelity Bayesian Optimisation with Continuous Approximations
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.4
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.8
Differentially Private Learning of Graphical Models using CGMs
Talk
Tue Aug 08 06:24 PM -- 06:42 PM (PDT) @ C4.6 & C4.7
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
In
Healthcare
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ Darling Harbour Theatre
Efficient softmax approximation for GPUs
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ Parkside 1
Multichannel End-to-end Speech Recognition
In
Language 1
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.5
Local Bayesian Optimization of Motor Skills
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.9& C4.10
Improving Gibbs Sampler Scan Quality with DoGS
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.1
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.4
Robust Structured Estimation with Single-Index Models
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.8
Minimizing Trust Leaks for Robust Sybil Detection
Talk
Tue Aug 08 06:42 PM -- 07:00 PM (PDT) @ C4.6 & C4.7
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
In
Healthcare
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ Darling Harbour Theatre
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ Parkside 1
Latent Intention Dialogue Models
In
Language 2
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ Parkside 2
Robust Guarantees of Stochastic Greedy Algorithms
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.5
Count-Based Exploration with Neural Density Models
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.9& C4.10
Magnetic Hamiltonian Monte Carlo
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.1
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.4
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.8
The Price of Differential Privacy For Online Learning
Talk
Tue Aug 08 08:30 PM -- 08:48 PM (PDT) @ C4.6 & C4.7
Bidirectional learning for time-series models with hidden units
In
Time series
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ Darling Harbour Theatre
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ Parkside 1
Discovering Discrete Latent Topics with Neural Variational Inference
In
Language 2
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ Parkside 2
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.5
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.9& C4.10
Probabilistic Path Hamiltonian Monte Carlo
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.1
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.4
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.8
Pain-Free Random Differential Privacy with Sensitivity Sampling
Talk
Tue Aug 08 08:48 PM -- 09:06 PM (PDT) @ C4.6 & C4.7
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
In
Time series
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ Darling Harbour Theatre
Variational Dropout Sparsifies Deep Neural Networks
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ Parkside 1
Toward Controlled Generation of Text
In
Language 2
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ Parkside 2
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.5
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.9& C4.10
Stochastic Gradient Monomial Gamma Sampler
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.1
Cost-Optimal Learning of Causal Graphs
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.4
Algebraic Variety Models for High-Rank Matrix Completion
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.8
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Talk
Tue Aug 08 09:06 PM -- 09:24 PM (PDT) @ C4.6 & C4.7
Coherent probabilistic forecasts for hierarchical time series
In
Time series
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ Darling Harbour Theatre
Unimodal Probability Distributions for Deep Ordinal Classification
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ Parkside 2
Probabilistic Submodular Maximization in Sub-Linear Time
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.5
The Predictron: End-To-End Learning and Planning
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.9& C4.10
Stochastic Gradient MCMC Methods for Hidden Markov Models
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.1
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.4
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.8
Differentially Private Chi-squared Test by Unit Circle Mechanism
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ C4.6 & C4.7
Soft-DTW: a Differentiable Loss Function for Time-Series
In
Time series
Talk
Tue Aug 08 09:24 PM -- 09:42 PM (PDT) @ Parkside 1
Learning Continuous Semantic Representations of Symbolic Expressions
In
Language 2
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ Parkside 1
Adversarial Feature Matching for Text Generation
In
Language 2
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ Parkside 2
On Approximation Guarantees for Greedy Low Rank Optimization
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ C4.5
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ C4.9& C4.10
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ C4.1
Estimating individual treatment effect: generalization bounds and algorithms
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ C4.8
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Talk
Tue Aug 08 09:42 PM -- 10:00 PM (PDT) @ C4.6 & C4.7
Variational Policy for Guiding Point Processes
In
Time series
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ Darling Harbour Theatre
Dance Dance Convolution
In
Applications
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ Parkside 1
Language Modeling with Gated Convolutional Networks
In
Language 3
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ Parkside 2
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.5
FeUdal Networks for Hierarchical Reinforcement Learning
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.9& C4.10
Distributed Batch Gaussian Process Optimization
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.1
Recursive Partitioning for Personalization using Observational Data
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.4
Optimal Densification for Fast and Accurate Minwise Hashing
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.8
An Adaptive Test of Independence with Analytic Kernel Embeddings
Talk
Tue Aug 08 10:30 PM -- 10:48 PM (PDT) @ C4.6 & C4.7
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ Darling Harbour Theatre
World of Bits: An Open-Domain Platform for Web-Based Agents
In
Applications
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ Parkside 1
Convolutional Sequence to Sequence Learning
In
Language 3
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ Parkside 2
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.5
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.9& C4.10
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.1
Identifying Best Interventions through Online Importance Sampling
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.4
Stochastic Generative Hashing
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.8
Sliced Wasserstein Kernel for Persistence Diagrams
Talk
Tue Aug 08 10:48 PM -- 11:06 PM (PDT) @ C4.6 & C4.7
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ Darling Harbour Theatre
Real-Time Adaptive Image Compression
In
Applications
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ Parkside 1
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
In
Language 3
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ Parkside 2
Near-Optimal Design of Experiments via Regret Minimization
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.5
Neural Episodic Control
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.9& C4.10
Random Feature Expansions for Deep Gaussian Processes
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.1
Deep IV: A Flexible Approach for Counterfactual Prediction
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.4
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.8
Adapting Kernel Representations Online Using Submodular Maximization
Talk
Tue Aug 08 11:06 PM -- 11:24 PM (PDT) @ C4.6 & C4.7
End-to-End Learning for Structured Prediction Energy Networks
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ Darling Harbour Theatre
Neural Message Passing for Quantum Chemistry
In
Applications
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ Parkside 1
Grammar Variational Autoencoder
In
Language 3
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ Parkside 2
Robust Budget Allocation via Continuous Submodular Functions
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.5
Neural Optimizer Search using Reinforcement Learning
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.9& C4.10
Asynchronous Distributed Variational Gaussian Processes for Regression
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.1
Counterfactual Data-Fusion for Online Reinforcement Learners
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.4
Large-Scale Evolution of Image Classifiers
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.8
Spherical Structured Feature Maps for Kernel Approximation
Talk
Tue Aug 08 11:24 PM -- 11:42 PM (PDT) @ C4.6 & C4.7
A Unified View of Multi-Label Performance Measures
Talk
Tue Aug 08 11:42 PM -- 12:00 AM (PDT) @ Darling Harbour Theatre
Accelerating Eulerian Fluid Simulation With Convolutional Networks
In
Applications
Talk
Tue Aug 08 11:42 PM -- 12:00 AM (PDT) @ Parkside 2
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Talk
Tue Aug 08 11:42 PM -- 12:00 AM (PDT) @ C4.9& C4.10
High Dimensional Bayesian Optimization with Elastic Gaussian Process
Talk
Tue Aug 08 11:42 PM -- 12:00 AM (PDT) @ C4.8
Nyström Method with Kernel K-means++ Samples as Landmarks
Talk
Tue Aug 08 11:42 PM -- 12:00 AM (PDT) @ C4.6 & C4.7
Scalable Generative Models for Multi-label Learning with Missing Labels
Invited Talk
Wed Aug 09 12:15 AM -- 01:15 AM (PDT) @ Darling Harbour Theatre
How AI Designers will Dictate Our Civic Future
[
Video]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #1
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
In
Posters Wed
[
PDF]
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Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #2
Estimating the unseen from multiple populations
In
Posters Wed
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PDF]
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Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #3
Meritocratic Fairness for Cross-Population Selection
In
Posters Wed
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PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #4
Neural networks and rational functions
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #5
Input Convex Neural Networks
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #6
Co-clustering through Optimal Transport
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #7
OptNet: Differentiable Optimization as a Layer in Neural Networks
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #8
Multiple Clustering Views from Multiple Uncertain Experts
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #9
Parseval Networks: Improving Robustness to Adversarial Examples
In
Posters Wed
[
PDF]
[
Summary/Notes]
Summary/Notes]
Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #10
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
In
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #11
Regularising Non-linear Models Using Feature Side-information
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #12
Clustering High Dimensional Dynamic Data Streams
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #13
Fast k-Nearest Neighbour Search via Prioritized DCI
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #14
Deep Spectral Clustering Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #15
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #16
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #17
Device Placement Optimization with Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #18
Dynamic Word Embeddings
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #19
Asynchronous Stochastic Gradient Descent with Delay Compensation
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #20
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #21
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #22
Preferential Bayesian Optmization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #23
Being Robust (in High Dimensions) Can Be Practical
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #24
Differentially Private Ordinary Least Squares
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #25
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #26
Deep Tensor Convolution on Multicores
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #27
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #28
Adaptive Consensus ADMM for Distributed Optimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #29
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #30
Stochastic Bouncy Particle Sampler
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #31
Max-value Entropy Search for Efficient Bayesian Optimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #32
Multilabel Classification with Group Testing and Codes
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #33
Priv’IT: Private and Sample Efficient Identity Testing
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #34
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #35
MEC: Memory-efficient Convolution for Deep Neural Network
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #36
Coupling Distributed and Symbolic Execution for Natural Language Queries
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #37
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #38
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #39
Canopy --- Fast Sampling with Cover Trees
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #40
Bayesian Optimization with Tree-structured Dependencies
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #41
High-Dimensional Structured Quantile Regression
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #42
Differentially Private Submodular Maximization: Data Summarization in Disguise
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #43
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #44
Beyond Filters: Compact Feature Map for Portable Deep Model
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #45
Image-to-Markup Generation with Coarse-to-Fine Attention
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #46
Projection-free Distributed Online Learning in Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #47
Learning Stable Stochastic Nonlinear Dynamical Systems
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #48
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #49
Multi-fidelity Bayesian Optimisation with Continuous Approximations
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #50
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #51
Differentially Private Learning of Graphical Models using CGMs
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #52
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #53
Efficient softmax approximation for GPUs
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #54
Multichannel End-to-end Speech Recognition
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #55
Local Bayesian Optimization of Motor Skills
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #56
Improving Gibbs Sampler Scan Quality with DoGS
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #57
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #58
Robust Structured Estimation with Single-Index Models
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #59
Minimizing Trust Leaks for Robust Sybil Detection
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #60
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #61
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #62
Latent Intention Dialogue Models
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #63
Robust Guarantees of Stochastic Greedy Algorithms
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #64
Count-Based Exploration with Neural Density Models
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #65
Magnetic Hamiltonian Monte Carlo
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #66
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #67
Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #68
The Price of Differential Privacy For Online Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #69
Bidirectional learning for time-series models with hidden units
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #70
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #71
Discovering Discrete Latent Topics with Neural Variational Inference
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #72
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #73
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #74
Probabilistic Path Hamiltonian Monte Carlo
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #75
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #76
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #77
Pain-Free Random Differential Privacy with Sensitivity Sampling
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #78
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #79
Variational Dropout Sparsifies Deep Neural Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #80
Toward Controlled Generation of Text
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #81
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #82
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #83
Stochastic Gradient Monomial Gamma Sampler
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #84
Cost-Optimal Learning of Causal Graphs
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #85
Algebraic Variety Models for High-Rank Matrix Completion
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #86
Differentially Private Clustering in High-Dimensional Euclidean Spaces
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #87
Coherent probabilistic forecasts for hierarchical time series
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #88
Unimodal Probability Distributions for Deep Ordinal Classification
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #89
Adversarial Feature Matching for Text Generation
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #90
Probabilistic Submodular Maximization in Sub-Linear Time
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #91
The Predictron: End-To-End Learning and Planning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #92
Stochastic Gradient MCMC Methods for Hidden Markov Models
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #93
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #94
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #95
Differentially Private Chi-squared Test by Unit Circle Mechanism
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #96
Soft-DTW: a Differentiable Loss Function for Time-Series
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #97
Learning Continuous Semantic Representations of Symbolic Expressions
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #98
On Approximation Guarantees for Greedy Low Rank Optimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #99
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #100
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #101
Estimating individual treatment effect: generalization bounds and algorithms
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #102
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #103
Variational Policy for Guiding Point Processes
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #104
Dance Dance Convolution
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #105
Language Modeling with Gated Convolutional Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #106
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten"
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #107
FeUdal Networks for Hierarchical Reinforcement Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #108
Distributed Batch Gaussian Process Optimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #109
Recursive Partitioning for Personalization using Observational Data
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #110
Optimal Densification for Fast and Accurate Minwise Hashing
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #111
An Adaptive Test of Independence with Analytic Kernel Embeddings
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #112
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #113
World of Bits: An Open-Domain Platform for Web-Based Agents
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #114
Convolutional Sequence to Sequence Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #115
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #116
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #117
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #118
Identifying Best Interventions through Online Importance Sampling
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #119
Stochastic Generative Hashing
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #120
Sliced Wasserstein Kernel for Persistence Diagrams
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #121
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #122
Real-Time Adaptive Image Compression
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #123
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #124
Near-Optimal Design of Experiments via Regret Minimization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #125
Neural Episodic Control
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #126
Random Feature Expansions for Deep Gaussian Processes
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #127
Deep IV: A Flexible Approach for Counterfactual Prediction
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #128
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #129
Adapting Kernel Representations Online Using Submodular Maximization
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #130
End-to-End Learning for Structured Prediction Energy Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #131
Neural Message Passing for Quantum Chemistry
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Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #132
Grammar Variational Autoencoder
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #133
Robust Budget Allocation via Continuous Submodular Functions
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #134
Neural Optimizer Search using Reinforcement Learning
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Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #135
Asynchronous Distributed Variational Gaussian Processes for Regression
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #136
Counterfactual Data-Fusion for Online Reinforcement Learners
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #137
Large-Scale Evolution of Image Classifiers
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #138
Spherical Structured Feature Maps for Kernel Approximation
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Poster
Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #139
A Unified View of Multi-Label Performance Measures
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #140
Accelerating Eulerian Fluid Simulation With Convolutional Networks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #141
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #142
High Dimensional Bayesian Optimization with Elastic Gaussian Process
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #143
Nyström Method with Kernel K-means++ Samples as Landmarks
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Wed Aug 09 01:30 AM -- 05:00 AM (PDT) @ Gallery #144
Scalable Generative Models for Multi-label Learning with Missing Labels
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Break
Wed Aug 09 07:00 AM -- 06:00 PM (PDT) @ Ground Level
Registration Desk
Break
Wed Aug 09 08:15 AM -- 09:00 AM (PDT) @ Gallery
Coffee Break
Break
Wed Aug 09 10:00 AM -- 10:30 AM (PDT) @ The Gallery
Coffee Break
Break
Wed Aug 09 12:00 PM -- 01:30 PM (PDT) @ Parkside 1
Open Business Meeting
Break
Wed Aug 09 12:00 PM -- 01:30 PM (PDT)
Lunch on your own
Break
Wed Aug 09 03:00 PM -- 03:30 PM (PDT) @ The Gallery
Coffee Break
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.8
Workshop on Human Interpretability in Machine Learning (WHI)
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.7
ML on a budget: IoT, Mobile and other tiny-ML applications
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.10
ICML Workshop on Machine Learning for Autonomous Vehicles 2017
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.3
Workshop on Visualization for Deep Learning
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.6
Video Games and Machine Learning
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.11
Learning to Generate Natural Language
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.1
Lifelong Learning: A Reinforcement Learning Approach
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ Parkside 1
Implicit Generative Models
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.9
Automatic Machine Learning (AutoML 2017)
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.4
Workshop on Computational Biology
Workshop
Wed Aug 09 03:30 PM -- 12:30 AM (PDT) @ C4.5
Principled Approaches to Deep Learning
Break
Wed Aug 09 06:15 PM -- 08:00 PM (PDT) @ Ballroom
Closing Reception
Break
Thu Aug 10 07:00 AM -- 06:00 PM (PDT) @ Ground Level
Registration Desk
Break
Thu Aug 10 08:00 AM -- 08:30 AM (PDT) @ Gallery
Coffee Break
Break
Thu Aug 10 10:00 AM -- 10:30 AM (PDT) @ Gallery
Coffee Break
Break
Thu Aug 10 12:00 PM -- 02:00 PM (PDT) @ On your own
Lunch - on your own
Break
Thu Aug 10 03:00 PM -- 03:30 PM (PDT) @ Gallery
Coffee Break
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.4
Private and Secure Machine Learning
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.6
Picky Learners: Choosing Alternative Ways to Process Data.
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.8
Human in the Loop Machine Learning
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.10
Reproducibility in Machine Learning Research
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.11
Interactive Machine Learning and Semantic Information Retrieval
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.7
Reliable Machine Learning in the Wild
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ Parkside 1
Reinforcement Learning Workshop
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.9
Machine Learning for Music Discovery
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.1
Time Series Workshop
Workshop
Thu Aug 10 03:30 PM -- 12:30 AM (PDT) @ C4.3
Machine Learning in Speech and Language Processing
Break
Fri Aug 11 07:00 AM -- 12:00 PM (PDT) @ Ground Level
Registration Desk
Break
Fri Aug 11 08:00 AM -- 08:30 AM (PDT) @ Gallery
Coffee Break
Workshop
Fri Aug 11 08:30 AM -- 05:30 PM (PDT) @ C4.5
Deep Structured Prediction
Break
Fri Aug 11 10:00 AM -- 10:30 AM (PDT) @ Gallery
Coffee Break
Break
Fri Aug 11 12:00 PM -- 02:00 PM (PDT) @ On your own
Lunch - on your own
Break
Fri Aug 11 03:00 PM -- 03:30 PM (PDT) @ Gallery
Coffee Break