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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #1
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #2
Variational Laplace Autoencoders
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #3
Latent Normalizing Flows for Discrete Sequences
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #4
Multi-objective training of Generative Adversarial Networks with multiple discriminators
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #5
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #6
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #7
Graphite: Iterative Generative Modeling of Graphs
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #9
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #10
On Scalable and Efficient Computation of Large Scale Optimal Transport
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #11
Understanding and correcting pathologies in the training of learned optimizers
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #12
Demystifying Dropout
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #13
Ladder Capsule Network
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #14
Unreproducible Research is Reproducible
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #15
Geometric Scattering for Graph Data Analysis
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #16
Robust Inference via Generative Classifiers for Handling Noisy Labels
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #17
LIT: Learned Intermediate Representation Training for Model Compression
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #18
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #19
What is the Effect of Importance Weighting in Deep Learning?
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #20
Similarity of Neural Network Representations Revisited
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #21
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #22
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #23
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #24
Multi-Object Representation Learning with Iterative Variational Inference
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #25
Cross-Domain 3D Equivariant Image Embeddings
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #26
Loss Landscapes of Regularized Linear Autoencoders
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #27
Hyperbolic Disk Embeddings for Directed Acyclic Graphs
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #28
LatentGNN: Learning Efficient Non-local Relations for Visual Recognition
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #29
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #30
Lorentzian Distance Learning for Hyperbolic Representations
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #31
Batch Policy Learning under Constraints
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #32
Quantifying Generalization in Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #33
Learning Latent Dynamics for Planning from Pixels
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #34
Projections for Approximate Policy Iteration Algorithms
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #35
Learning Structured Decision Problems with Unawareness
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #36
Calibrated Model-Based Deep Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #37
Reinforcement Learning in Configurable Continuous Environments
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #38
Target-Based Temporal-Difference Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #39
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #40
Finding Options that Minimize Planning Time
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #41
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #42
Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #43
Meta-Learning Neural Bloom Filters
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #44
CoT: Cooperative Training for Generative Modeling of Discrete Data
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #45
Non-Monotonic Sequential Text Generation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #46
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #47
Empirical Analysis of Beam Search Performance Degradation in Neural Sequence Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #48
Trainable Decoding of Sets of Sequences for Neural Sequence Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #49
Learning to Generalize from Sparse and Underspecified Rewards
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #50
Efficient Training of BERT by Progressively Stacking
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #51
Decentralized Exploration in Multi-Armed Bandits
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #52
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #53
Exploiting structure of uncertainty for efficient matroid semi-bandits
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #54
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #55
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #56
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #57
TarMAC: Targeted Multi-Agent Communication
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #58
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #59
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #60
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #61
Neural Network Attributions: A Causal Perspective
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #62
Towards a Deep and Unified Understanding of Deep Neural Models in NLP
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #63
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #64
Functional Transparency for Structured Data: a Game-Theoretic Approach
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #65
Exploring interpretable LSTM neural networks over multi-variable data
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #66
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #67
Gaining Free or Low-Cost Interpretability with Interpretable Partial Substitute
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #68
State-Regularized Recurrent Neural Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #69
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #70
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #71
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #72
On the Spectral Bias of Neural Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #73
Recursive Sketches for Modular Deep Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #74
Zero-Shot Knowledge Distillation in Deep Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #75
A Convergence Theory for Deep Learning via Over-Parameterization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #76
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #77
Approximation and non-parametric estimation of ResNet-type convolutional neural networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #78
Global Convergence of Block Coordinate Descent in Deep Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #79
Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #80
On the Limitations of Representing Functions on Sets
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #81
Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #82
Nonparametric Bayesian Deep Networks with Local Competition
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #83
Good Initializations of Variational Bayes for Deep Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #84
Dropout as a Structured Shrinkage Prior
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #85
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #86
On Variational Bounds of Mutual Information
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #87
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #88
Hierarchical Importance Weighted Autoencoders
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #89
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #90
Understanding Priors in Bayesian Neural Networks at the Unit Level
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #91
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #92
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #93
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #94
Width Provably Matters in Optimization for Deep Linear Neural Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #95
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #96
Power k-Means Clustering
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #97
Distributed Learning over Unreliable Networks
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #98
Escaping Saddle Points with Adaptive Gradient Methods
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #99
$\texttt{DoubleSqueeze}$: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #100
Model Function Based Conditional Gradient Method with Armijo-like Line Search
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #101
Analogies Explained: Towards Understanding Word Embeddings
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #102
Parameter-Efficient Transfer Learning for NLP
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #103
Efficient On-Device Models using Neural Projections
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #104
Deep Residual Output Layers for Neural Language Generation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #105
Improving Neural Language Modeling via Adversarial Training
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #106
Mixture Models for Diverse Machine Translation: Tricks of the Trade
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #107
MASS: Masked Sequence to Sequence Pre-training for Language Generation
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #108
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #109
MeanSum: A Neural Model for Unsupervised Multi-Document Abstractive Summarization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #110
CHiVE: Varying Prosody in Speech Synthesis with a Linguistically Driven Dynamic Hierarchical Conditional Variational Network
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #111
COMIC: Multi-view Clustering Without Parameter Selection
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #112
The Wasserstein Transform
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #113
Sequential Facility Location: Approximate Submodularity and Greedy Algorithm
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #114
Neural Collaborative Subspace Clustering
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #115
Unsupervised Deep Learning by Neighbourhood Discovery
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #116
Autoregressive Energy Machines
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #117
Greedy Orthogonal Pivoting Algorithm for Non-Negative Matrix Factorization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #118
Noise2Self: Blind Denoising by Self-Supervision
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #119
Learning Dependency Structures for Weak Supervision Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #120
Geometry and Symmetry in Short-and-Sparse Deconvolution
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #121
On Sparse Linear Regression in the Local Differential Privacy Model
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #122
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #123
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #124
Differentially Private Learning of Geometric Concepts
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #125
Toward Controlling Discrimination in Online Ad Auctions
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #126
Learning Optimal Fair Policies
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #127
Fairness-Aware Learning for Continuous Attributes and Treatments
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #128
Fairness risk measures
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #129
Proportionally Fair Clustering
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #130
Stable and Fair Classification
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #131
Flexibly Fair Representation Learning by Disentanglement
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #132
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #133
Fairness without Harm: Decoupled Classifiers with Preference Guarantees
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #134
Differentially Private Fair Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #135
Obtaining Fairness using Optimal Transport Theory
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #136
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #137
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #138
Making Decisions that Reduce Discriminatory Impacts
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #139
Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #140
Online Algorithms for Rent-Or-Buy with Expert Advice
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #141
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #142
Categorical Feature Compression via Submodular Optimization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #143
Multi-Frequency Phase Synchronization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #144
Faster Algorithms for Binary Matrix Factorization
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #146
Guided evolutionary strategies: augmenting random search with surrogate gradients
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #147
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #148
Semi-Cyclic Stochastic Gradient Descent
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #149
Matrix-Free Preconditioning in Online Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #150
Online Convex Optimization in Adversarial Markov Decision Processes
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #151
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #152
Online Learning with Sleeping Experts and Feedback Graphs
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #153
Incremental Randomized Sketching for Online Kernel Learning
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #154
Adaptive Scale-Invariant Online Algorithms for Learning Linear Models
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #155
Online Control with Adversarial Disturbances
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #156
Adversarial Online Learning with noise
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #157
Online Variance Reduction with Mixtures
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #158
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #159
Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #160
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #161
Adaptive Regret of Convex and Smooth Functions
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Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #162
Online Adaptive Principal Component Analysis and Its extensions
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #163
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #164
Anytime Online-to-Batch, Optimism and Acceleration
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #165
Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #166
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #167
Adaptive Sensor Placement for Continuous Spaces
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #168
Scale-free adaptive planning for deterministic dynamics & discounted rewards
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #169
Communication-Constrained Inference and the Role of Shared Randomness
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #170
Learning and Data Selection in Big Datasets
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #171
Sublinear quantum algorithms for training linear and kernel-based classifiers
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #172
Agnostic Federated Learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #173
Discovering Conditionally Salient Features with Statistical Guarantees
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #174
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #175
The information-theoretic value of unlabeled data in semi-supervised learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #176
Unsupervised Label Noise Modeling and Loss Correction
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #177
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #178
Pareto Optimal Streaming Unsupervised Classification
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #179
Geometric Losses for Distributional Learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #180
Classification from Positive, Unlabeled and Biased Negative Data
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #181
Complementary-Label Learning for Arbitrary Losses and Models
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #182
Learning to Infer Program Sketches
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #183
Hierarchically Structured Meta-learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #184
Bridging Theory and Algorithm for Domain Adaptation
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #185
Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #186
Learning What and Where to Transfer
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #187
DBSCAN++: Towards fast and scalable density clustering
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #188
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #189
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #190
Spectral Clustering of Signed Graphs via Matrix Power Means
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #191
Coresets for Ordered Weighted Clustering
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #192
Fair k-Center Clustering for Data Summarization
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #193
A Better k-means++ Algorithm via Local Search
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #194
Kernel Normalized Cut: a Theoretical Revisit
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #195
Guarantees for Spectral Clustering with Fairness Constraints
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #196
Supervised Hierarchical Clustering with Exponential Linkage
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #197
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #198
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #199
Unifying Orthogonal Monte Carlo Methods
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #200
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #201
Metropolis-Hastings Generative Adversarial Networks
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #202
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #203
Replica Conditional Sequential Monte Carlo
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #204
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #205
Adaptive Antithetic Sampling for Variance Reduction
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #206
Accelerated Flow for Probability Distributions
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #207
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #208
Dimensionality Reduction for Tukey Regression
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #209
Efficient Full-Matrix Adaptive Regularization
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #210
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #211
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
In
Posters Thu
[
Video]
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #212
Robust Estimation of Tree Structured Gaussian Graphical Models
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #213
Spectral Approximate Inference
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #214
Partially Linear Additive Gaussian Graphical Models
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #215
DAG-GNN: DAG Structure Learning with Graph Neural Networks
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #216
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #217
Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #218
Linear-Complexity Data-Parallel Earth Mover's Distance Approximations
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #219
Model Comparison for Semantic Grouping
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #220
RaFM: Rank-Aware Factorization Machines
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #221
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #222
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #223
Neural Separation of Observed and Unobserved Distributions
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #224
Almost Unsupervised Text to Speech and Automatic Speech Recognition
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #225
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #226
A fully differentiable beam search decoder
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #227
Scaling Up Ordinal Embedding: A Landmark Approach
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #228
Learning to select for a predefined ranking
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #229
Mallows ranking models: maximum likelihood estimate and regeneration
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #230
Fast and Stable Maximum Likelihood Estimation for Incomplete Multinomial Models
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #231
Fast Algorithm for Generalized Multinomial Models with Ranking Data
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #232
Graph Resistance and Learning from Pairwise Comparisons
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #233
Learning Context-dependent Label Permutations for Multi-label Classification
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #234
Discovering Context Effects from Raw Choice Data
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #235
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
In
Posters Thu
Poster
Thu Jun 13 06:30 PM -- 09:00 PM (PDT) @ Pacific Ballroom #236
Learning Distance for Sequences by Learning a Ground Metric
In
Posters Thu