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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #2
Large-Scale Cox Process Inference using Variational Fourier Features
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #3
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #4
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #5
A Progressive Batching L-BFGS Method for Machine Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #6
WSNet: Compact and Efficient Networks Through Weight Sampling
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #7
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #8
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #9
Competitive Caching with Machine Learned Advice
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #10
Approximation Algorithms for Cascading Prediction Models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #11
Orthogonal Machine Learning: Power and Limitations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #12
Causal Bandits with Propagating Inference
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #13
Mix & Match - Agent Curricula for Reinforcement Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #14
The Uncertainty Bellman Equation and Exploration
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #15
Hierarchical Imitation and Reinforcement Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #16
Policy Optimization with Demonstrations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #17
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #18
Level-Set Methods for Finite-Sum Constrained Convex Optimization
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #19
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #20
A Boo(n) for Evaluating Architecture Performance
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #21
RLlib: Abstractions for Distributed Reinforcement Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #22
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #23
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #24
Sound Abstraction and Decomposition of Probabilistic Programs
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #25
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #26
Modeling Sparse Deviations for Compressed Sensing using Generative Models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #27
Revealing Common Statistical Behaviors in Heterogeneous Populations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #28
Improved nearest neighbor search using auxiliary information and priority functions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #29
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #30
QuantTree: Histograms for Change Detection in Multivariate Data Streams
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #31
An Iterative, Sketching-based Framework for Ridge Regression
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #32
Learning Low-Dimensional Temporal Representations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #33
Rapid Adaptation with Conditionally Shifted Neurons
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #34
PDE-Net: Learning PDEs from Data
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #35
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #36
Topological mixture estimation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #37
On Matching Pursuit and Coordinate Descent
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #38
Frank-Wolfe with Subsampling Oracle
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #39
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #40
Fourier Policy Gradients
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #41
Adaptive Three Operator Splitting
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #42
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #43
Learning Semantic Representations for Unsupervised Domain Adaptation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #44
Learning Adversarially Fair and Transferable Representations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #45
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #46
Efficient end-to-end learning for quantizable representations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #47
Solving Partial Assignment Problems using Random Clique Complexes
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #48
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #49
Convergence guarantees for a class of non-convex and non-smooth optimization problems
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #50
Estimation of Markov Chain via Rank-constrained Likelihood
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #51
Efficient First-Order Algorithms for Adaptive Signal Denoising
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #52
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #53
Noisin: Unbiased Regularization for Recurrent Neural Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #54
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #55
Disentangled Sequential Autoencoder
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #56
Stochastic Video Generation with a Learned Prior
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #57
Mutual Information Neural Estimation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #58
Adversarially Regularized Autoencoders
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #59
Policy Optimization as Wasserstein Gradient Flows
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #60
Self-Imitation Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #61
Spectrally Approximating Large Graphs with Smaller Graphs
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #62
On the Spectrum of Random Features Maps of High Dimensional Data
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #63
Learning Registered Point Processes from Idiosyncratic Observations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #64
Deep Bayesian Nonparametric Tracking
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #65
Learning and Memorization
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #66
Attention-based Deep Multiple Instance Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #67
Classification from Pairwise Similarity and Unlabeled Data
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #68
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #69
On the Implicit Bias of Dropout
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #70
Convolutional Imputation of Matrix Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #71
Detecting and Correcting for Label Shift with Black Box Predictors
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #72
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #73
Comparison-Based Random Forests
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #74
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #75
Provable Variable Selection for Streaming Features
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #76
Out-of-sample extension of graph adjacency spectral embedding
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #77
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #78
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #79
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #80
Optimization Landscape and Expressivity of Deep CNNs
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #81
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #82
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #83
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #84
Rectify Heterogeneous Models with Semantic Mapping
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #85
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #86
Iterative Amortized Inference
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #87
Blind Justice: Fairness with Encrypted Sensitive Attributes
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #88
Active Learning with Logged Data
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #89
A Reductions Approach to Fair Classification
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #90
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #91
Bayesian Model Selection for Change Point Detection and Clustering
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #92
A Unified Framework for Structured Low-rank Matrix Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #93
Firing Bandits: Optimizing Crowdfunding
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #94
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #95
Compiling Combinatorial Prediction Games
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #96
Rates of Convergence of Spectral Methods for Graphon Estimation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #97
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #98
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #99
StrassenNets: Deep Learning with a Multiplication Budget
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #100
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #101
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #102
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #103
Overcoming Catastrophic Forgetting with Hard Attention to the Task
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #104
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #105
Efficient Neural Audio Synthesis
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #106
Born Again Neural Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #107
Adaptive Sampled Softmax with Kernel Based Sampling
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #109
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #110
Autoregressive Quantile Networks for Generative Modeling
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #111
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #112
On the Limitations of First-Order Approximation in GAN Dynamics
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #113
Learning to Explore via Meta-Policy Gradient
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #114
Mean Field Multi-Agent Reinforcement Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #115
Online Linear Quadratic Control
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #116
Online Learning with Abstention
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #117
Celer: a Fast Solver for the Lasso with Dual Extrapolation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #118
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #119
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #120
Mixed batches and symmetric discriminators for GAN training
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #121
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #124
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #125
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #126
Communication-Computation Efficient Gradient Coding
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #127
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #128
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #129
On Nesting Monte Carlo Estimators
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #130
Stein Variational Gradient Descent Without Gradient
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #131
Detecting non-causal artifacts in multivariate linear regression models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #132
The Hierarchical Adaptive Forgetting Variational Filter
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #133
Junction Tree Variational Autoencoder for Molecular Graph Generation
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #134
Semi-Amortized Variational Autoencoders
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #135
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #136
Semiparametric Contextual Bandits
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #137
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #138
Weightless: Lossy weight encoding for deep neural network compression
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #139
Parallel Bayesian Network Structure Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #140
Temporal Poisson Square Root Graphical Models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #141
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #142
Dynamic Regret of Strongly Adaptive Methods
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #143
Distributed Clustering via LSH Based Data Partitioning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #145
Minibatch Gibbs Sampling on Large Graphical Models
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #146
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #147
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #148
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #149
Pathwise Derivatives Beyond the Reparameterization Trick
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #150
Message Passing Stein Variational Gradient Descent
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #151
State Space Gaussian Processes with Non-Gaussian Likelihood
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #152
Constant-Time Predictive Distributions for Gaussian Processes
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #153
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #154
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #155
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #156
Probably Approximately Metric-Fair Learning
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #157
Neural Program Synthesis from Diverse Demonstration Videos
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #158
Video Prediction with Appearance and Motion Conditions
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #159
CRVI: Convex Relaxation for Variational Inference
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #160
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #161
Transformation Autoregressive Networks
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #162
Learning equations for extrapolation and control
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Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #163
Analyzing Uncertainty in Neural Machine Translation
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #164
Hierarchical Text Generation and Planning for Strategic Dialogue
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #165
Budgeted Experiment Design for Causal Structure Learning
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #166
Accurate Inference for Adaptive Linear Models
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #167
Path-Level Network Transformation for Efficient Architecture Search
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #168
Progress & Compress: A scalable framework for continual learning
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #169
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #170
Understanding and Simplifying One-Shot Architecture Search
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #171
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #172
State Abstractions for Lifelong Reinforcement Learning
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #173
Bounding and Counting Linear Regions of Deep Neural Networks
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #175
Clipped Action Policy Gradient
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #176
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #177
Inter and Intra Topic Structure Learning with Word Embeddings
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #178
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #179
The Hidden Vulnerability of Distributed Learning in Byzantium
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Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #180
Asynchronous Byzantine Machine Learning (the case of SGD)
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