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Tutorial
Mon Dec 07 06:30 AM -- 08:30 AM (PST) @ Level 2 room 210 AB
Deep Learning
Tutorial
Mon Dec 07 06:30 AM -- 08:30 AM (PST) @ Level 2 room 210 E,F
Large-Scale Distributed Systems for Training Neural Networks
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Slides]
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Break
Mon Dec 07 08:00 AM -- 09:30 AM (PST) @ 220 A
Breakfast
Tutorial
Mon Dec 07 10:00 AM -- 12:00 PM (PST) @ Level 2 room 210 E,F
Probabilistic Programming
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Slides]
Tutorial
Mon Dec 07 10:00 AM -- 12:00 PM (PST) @ Level 2 room 210 AB
Monte Carlo Inference Methods
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Slides]
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Break
Mon Dec 07 10:45 AM -- 11:15 AM (PST) @ 210 C
Coffee Break
Tutorial
Mon Dec 07 12:30 PM -- 02:30 PM (PST) @ Level 2 room 210 E,F
High-Performance Hardware for Machine Learning
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Slides]
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Tutorial
Mon Dec 07 12:30 PM -- 02:30 PM (PST) @ Level 2 room 210 AB
Introduction to Reinforcement Learning with Function Approximation
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Slides]
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Break
Mon Dec 07 03:00 PM -- 03:30 PM (PST) @ 210 C
Coffee Break
Session
Mon Dec 07 03:30 PM -- 03:55 PM (PST) @ 210 AB
Opening Remarks, Awards and Reception
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #1
Texture Synthesis Using Convolutional Neural Networks
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #2
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #4
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Generative Image Modeling Using Spatial LSTMs
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #6
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #7
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #8
Exploring Models and Data for Image Question Answering
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #9
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #10
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #11
Learning From Small Samples: An Analysis of Simple Decision Heuristics
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #12
3D Object Proposals for Accurate Object Class Detection
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #15
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #16
Learning to Transduce with Unbounded Memory
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #17
Spectral Representations for Convolutional Neural Networks
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #18
A Theory of Decision Making Under Dynamic Context
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #19
Bidirectional Recurrent Neural Networks as Generative Models
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #20
Recognizing retinal ganglion cells in the dark
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #21
A Recurrent Latent Variable Model for Sequential Data
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #23
Deep Temporal Sigmoid Belief Networks for Sequence Modeling
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #24
Hidden Technical Debt in Machine Learning Systems
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Statistical Model Criticism using Kernel Two Sample Tests
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #27
A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #28
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #29
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #30
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Learning spatiotemporal trajectories from manifold-valued longitudinal data
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Variational Dropout and the Local Reparameterization Trick
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #36
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Fast Second Order Stochastic Backpropagation for Variational Inference
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #39
Rethinking LDA: Moment Matching for Discrete ICA
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Model-Based Relative Entropy Stochastic Search
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #41
Supervised Learning for Dynamical System Learning
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Expectation Particle Belief Propagation
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Embedding Inference for Structured Multilabel Prediction
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Tractable Learning for Complex Probability Queries
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #46
Local Expectation Gradients for Black Box Variational Inference
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #48
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Fast and Accurate Inference of Plackett–Luce Models
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #50
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #52
M-Statistic for Kernel Change-Point Detection
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #53
Fast Two-Sample Testing with Analytic Representations of Probability Measures
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Adversarial Prediction Games for Multivariate Losses
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #57
Rate-Agnostic (Causal) Structure Learning
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Online Prediction at the Limit of Zero Temperature
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #59
Lifted Symmetry Detection and Breaking for MAP Inference
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Bandits with Unobserved Confounders: A Causal Approach
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #61
Sample Complexity Bounds for Iterative Stochastic Policy Optimization
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #62
Basis refinement strategies for linear value function approximation in MDPs
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #63
Probabilistic Variational Bounds for Graphical Models
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #64
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #65
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #67
GAP Safe screening rules for sparse multi-task and multi-class models
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Decomposition Bounds for Marginal MAP
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #69
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Estimating Mixture Models via Mixtures of Polynomials
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #71
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #75
Subspace Clustering with Irrelevant Features via Robust Dantzig Selector
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #76
A class of network models recoverable by spectral clustering
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #77
Monotone k-Submodular Function Maximization with Size Constraints
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Smooth and Strong: MAP Inference with Linear Convergence
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #79
StopWasting My Gradients: Practical SVRG
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #81
Differentially Private Learning of Structured Discrete Distributions
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #83
Bayesian Optimization with Exponential Convergence
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #84
Fast Randomized Kernel Ridge Regression with Statistical Guarantees
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms
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Poster
Mon Dec 07 04:00 PM (PST) @ 210 C #86
Beyond Convexity: Stochastic Quasi-Convex Optimization
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #87
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #89
Black-box optimization of noisy functions with unknown smoothness
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #92
Sum-of-Squares Lower Bounds for Sparse PCA
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #94
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Convergence Analysis of Prediction Markets via Randomized Subspace Descent
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #96
Accelerated Proximal Gradient Methods for Nonconvex Programming
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Communication Complexity of Distributed Convex Learning and Optimization
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #100
Explore no more: Improved high-probability regret bounds for non-stochastic bandits
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #101
A Nonconvex Optimization Framework for Low Rank Matrix Estimation
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #102
Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability
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Oral
Tue Dec 08 06:50 AM -- 07:10 AM (PST) @ Room 210 A
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Minimum Weight Perfect Matching via Blossom Belief Propagation
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Super-Resolution Off the Grid
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
b-bit Marginal Regression
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Optimal Rates for Random Fourier Features
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Submodular Hamming Metrics
Spotlight
Tue Dec 08 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Top-k Multiclass SVM
Oral
Tue Dec 08 07:55 AM -- 08:35 AM (PST) @ Room 210 A
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Oral
Tue Dec 08 07:55 AM -- 08:35 AM (PST) @ Room 210 A
Sampling from Probabilistic Submodular Models
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Distributionally Robust Logistic Regression
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
On some provably correct cases of variational inference for topic models
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Extending Gossip Algorithms to Distributed Estimation of U-statistics
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
The Self-Normalized Estimator for Counterfactual Learning
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Spotlight
Tue Dec 08 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Break
Tue Dec 08 10:35 AM -- 10:55 AM (PST) @ 210 A
Coffee Break
Oral
Tue Dec 08 11:50 AM -- 12:30 PM (PST) @ Room 210 A
Probabilistic Line Searches for Stochastic Optimization
Oral
Tue Dec 08 11:50 AM -- 12:30 PM (PST) @ Room 210 A
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
Break
Tue Dec 08 12:00 PM -- 02:00 PM (PST) @ 210 A
Lunch Break
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Latent Bayesian melding for integrating individual and population models
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Automatic Variational Inference in Stan
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Data Generation as Sequential Decision Making
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Stochastic Expectation Propagation
Spotlight
Tue Dec 08 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Deep learning with Elastic Averaging SGD
Oral
Tue Dec 08 01:30 PM -- 02:30 PM (PST) @ Room 210 A
Competitive Distribution Estimation: Why is Good-Turing Good
Oral
Tue Dec 08 01:30 PM -- 02:30 PM (PST) @ Room 210 A
Fast Convergence of Regularized Learning in Games
Oral
Tue Dec 08 01:30 PM -- 02:30 PM (PST) @ Room 210 A
Interactive Control of Diverse Complex Characters with Neural Networks
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
The Human Kernel
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
On the Pseudo-Dimension of Nearly Optimal Auctions
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
High-dimensional neural spike train analysis with generalized count linear dynamical systems
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
Measuring Sample Quality with Stein's Method
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
Biologically Inspired Dynamic Textures for Probing Motion Perception
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
Closed-form Estimators for High-dimensional Generalized Linear Models
Spotlight
Tue Dec 08 02:30 PM -- 03:00 PM (PST) @ Room 210 A
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Break
Tue Dec 08 04:00 PM -- 04:30 PM (PST) @ 210 A
Coffee Break
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
Claudico: The World's Strongest No-Limit Texas Hold'em Poker AI
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
An interactive system for the extraction of meaningful visualizations from high-dimensional data
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
Fast sampling with neuromorphic hardware
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
Deep Learning using Approximate Hardware
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
DIANNE - Distributed Artificial Neural Networks
Demonstration
Tue Dec 08 04:00 PM -- 08:55 PM (PST) @ 210D
Vitruvian Science: a visual editor for quickly building neural networks in the cloud
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #1
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #2
Shepard Convolutional Neural Networks
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #3
Learning Structured Output Representation using Deep Conditional Generative Models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #4
Expressing an Image Stream with a Sequence of Natural Sentences
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Visalogy: Answering Visual Analogy Questions
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #6
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #7
SubmodBoxes: Near-Optimal Search for a Set of Diverse Object Proposals
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #8
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #9
Learning visual biases from human imagination
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #10
Character-level Convolutional Networks for Text Classification
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #12
Learning both Weights and Connections for Efficient Neural Network
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #13
Interactive Control of Diverse Complex Characters with Neural Networks
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Biologically Inspired Dynamic Textures for Probing Motion Perception
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #15
Unsupervised Learning by Program Synthesis
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #17
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #19
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #20
The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #21
Unlocking neural population non-stationarities using hierarchical dynamics models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #22
Deeply Learning the Messages in Message Passing Inference
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #23
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Latent Bayesian melding for integrating individual and population models
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #26
High-dimensional neural spike train analysis with generalized count linear dynamical systems
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #27
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #28
The Population Posterior and Bayesian Modeling on Streams
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #29
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #30
Preconditioned Spectral Descent for Deep Learning
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Learning Continuous Control Policies by Stochastic Value Gradients
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Automatic Variational Inference in Stan
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #35
Data Generation as Sequential Decision Making
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #37
Deep learning with Elastic Averaging SGD
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Learning with Group Invariant Features: A Kernel Perspective.
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #39
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Probabilistic Line Searches for Stochastic Optimization
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #41
A hybrid sampler for Poisson-Kingman mixture models
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Reflection, Refraction, and Hamiltonian Monte Carlo
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Planar Ultrametrics for Image Segmentation
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Learning Bayesian Networks with Thousands of Variables
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #46
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #47
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #48
On some provably correct cases of variational inference for topic models
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Large-scale probabilistic predictors with and without guarantees of validity
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #50
On the Accuracy of Self-Normalized Log-Linear Models
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Policy Evaluation Using the Ω-Return
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #52
Community Detection via Measure Space Embedding
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #53
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Inference for determinantal point processes without spectral knowledge
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #55
Sample Complexity of Learning Mahalanobis Distance Metrics
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Matrix Manifold Optimization for Gaussian Mixtures
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #57
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #59
The Self-Normalized Estimator for Counterfactual Learning
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Distributionally Robust Logistic Regression
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #63
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #64
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #65
Distributed Submodular Cover: Succinctly Summarizing Massive Data
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Parallel Correlation Clustering on Big Graphs
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #67
Fast Bidirectional Probability Estimation in Markov Models
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Evaluating the statistical significance of biclusters
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #69
Regularization Path of Cross-Validation Error Lower Bounds
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Sampling from Probabilistic Submodular Models
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Extending Gossip Algorithms to Distributed Estimation of U-statistics
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #73
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Collaboratively Learning Preferences from Ordinal Data
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #75
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #76
Alternating Minimization for Regression Problems with Vector-valued Outputs
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #77
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Subset Selection by Pareto Optimization
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #79
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Minimum Weight Perfect Matching via Blossom Belief Propagation
[
PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #82
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #83
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #84
On the Pseudo-Dimension of Nearly Optimal Auctions
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Closed-form Estimators for High-dimensional Generalized Linear Models
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #86
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #87
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Competitive Distribution Estimation: Why is Good-Turing Good
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PDF]
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #89
A Universal Primal-Dual Convex Optimization Framework
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #90
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Private Graphon Estimation for Sparse Graphs
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #92
HONOR: Hybrid Optimization for NOn-convex Regularized problems
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #93
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Optimal Rates for Random Fourier Features
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #97
Fast Convergence of Regularized Learning in Games
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Online Learning with Adversarial Delays
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #100
Structured Estimation with Atomic Norms: General Bounds and Applications
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PDF]
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #101
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
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PDF]
Oral
Wed Dec 09 06:50 AM -- 07:10 AM (PST) @ Room 210 A
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Optimal Testing for Properties of Distributions
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Information-theoretic lower bounds for convex optimization with erroneous oracles
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Accelerated Mirror Descent in Continuous and Discrete Time
Spotlight
Wed Dec 09 07:10 AM -- 07:35 AM (PST) @ Room 210 A
Adaptive Online Learning
Break
Wed Dec 09 07:30 AM -- 09:00 AM (PST) @ 220 A
Breakfast
Oral
Wed Dec 09 07:55 AM -- 08:35 AM (PST) @ Room 210 A
Deep Visual Analogy-Making
Oral
Wed Dec 09 07:55 AM -- 08:35 AM (PST) @ Room 210 A
End-To-End Memory Networks
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Attention-Based Models for Speech Recognition
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Where are they looking?
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Training Very Deep Networks
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Deep Convolutional Inverse Graphics Network
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Learning to Segment Object Candidates
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors
Spotlight
Wed Dec 09 08:35 AM -- 09:00 AM (PST) @ Room 210 A
Spatial Transformer Networks
Break
Wed Dec 09 10:35 AM -- 10:55 AM (PST) @ 210 A
Coffee Break
Invited Talk
Wed Dec 09 11:00 AM -- 11:50 AM (PST) @ Level 2 room 210 AB
Diagnosis and Therapy of Psychiatric Disorders Based on Brain Dynamics
Oral
Wed Dec 09 11:50 AM -- 12:30 PM (PST) @ Room 210 A
A Reduced-Dimension fMRI Shared Response Model
Oral
Wed Dec 09 11:50 AM -- 12:30 PM (PST) @ Room 210 A
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments
Break
Wed Dec 09 12:00 PM -- 02:00 PM (PST) @ 210 A
Lunch Break
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Action-Conditional Video Prediction using Deep Networks in Atari Games
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
On-the-Job Learning with Bayesian Decision Theory
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Learning Wake-Sleep Recurrent Attention Models
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Backpropagation for Energy-Efficient Neuromorphic Computing
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
Spotlight
Wed Dec 09 12:30 PM -- 01:00 PM (PST) @ Room 210 A
Color Constancy by Learning to Predict Chromaticity from Luminance
Oral
Wed Dec 09 02:20 PM -- 02:40 PM (PST) @ Room 210 A
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Spotlight
Wed Dec 09 02:40 PM -- 03:00 PM (PST) @ Room 210 A
Pointer Networks
Spotlight
Wed Dec 09 02:40 PM -- 03:00 PM (PST) @ Room 210 A
Precision-Recall-Gain Curves: PR Analysis Done Right
Spotlight
Wed Dec 09 02:40 PM -- 03:00 PM (PST) @ Room 210 A
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
Spotlight
Wed Dec 09 02:40 PM -- 03:00 PM (PST) @ Room 210 A
Structured Transforms for Small-Footprint Deep Learning
Spotlight
Wed Dec 09 02:40 PM -- 03:00 PM (PST) @ Room 210 A
Equilibrated adaptive learning rates for non-convex optimization
Break
Wed Dec 09 04:00 PM -- 04:30 PM (PST) @ 210 A
Coffee Break
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
Data-Driven Speech Animation
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
The pMMF multiresolution matrix factorization library
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
Interactive Incremental Question Answering
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
CodaLab Worksheets for Reproducible, Executable Papers
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
Accelerated Deep Learning on GPUs: From Large Scale Training to Embedded Deployment
Demonstration
Wed Dec 09 04:00 PM -- 08:55 PM (PST) @ 210D
Scaling up visual search for product recommendation
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Attention-Based Models for Speech Recognition
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #6
Deep Convolutional Inverse Graphics Network
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #8
Learning to Segment Object Candidates
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #9
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #10
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #11
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #12
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #13
Backpropagation for Energy-Efficient Neuromorphic Computing
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Learning Wake-Sleep Recurrent Attention Models
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #15
On-the-Job Learning with Bayesian Decision Theory
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #16
Color Constancy by Learning to Predict Chromaticity from Luminance
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #17
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #18
Action-Conditional Video Prediction using Deep Networks in Atari Games
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #19
Bayesian Active Model Selection with an Application to Automated Audiometry
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #20
Efficient and Robust Automated Machine Learning
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #21
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #23
A Reduced-Dimension fMRI Shared Response Model
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #24
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Precision-Recall-Gain Curves: PR Analysis Done Right
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #26
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #27
Equilibrated adaptive learning rates for non-convex optimization
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #28
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #30
MCMC for Variationally Sparse Gaussian Processes
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Streaming, Distributed Variational Inference for Bayesian Nonparametrics
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Human Memory Search as Initial-Visit Emitting Random Walk
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Structured Transforms for Small-Footprint Deep Learning
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #35
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #36
A Structural Smoothing Framework For Robust Graph Comparison
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #37
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Inverse Reinforcement Learning with Locally Consistent Reward Functions
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #39
Consistent Multilabel Classification
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Is Approval Voting Optimal Given Approval Votes?
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #41
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Efficient Non-greedy Optimization of Decision Trees
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Statistical Topological Data Analysis - A Kernel Perspective
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Softstar: Heuristic-Guided Probabilistic Inference
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #46
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #47
A Complete Recipe for Stochastic Gradient MCMC
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #48
Barrier Frank-Wolfe for Marginal Inference
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Practical and Optimal LSH for Angular Distance
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #50
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Kullback-Leibler Proximal Variational Inference
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #52
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #53
Streaming Min-max Hypergraph Partitioning
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Efficient Output Kernel Learning for Multiple Tasks
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #55
Gradient Estimation Using Stochastic Computation Graphs
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Lifted Inference Rules With Constraints
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #59
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #61
Segregated Graphs and Marginals of Chain Graph Models
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #62
Approximating Sparse PCA from Incomplete Data
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #63
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #64
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #65
Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Testing Closeness With Unequal Sized Samples
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #67
Learning Causal Graphs with Small Interventions
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Regret-Based Pruning in Extensive-Form Games
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #69
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Bounding errors of Expectation-Propagation
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #71
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Local Smoothness in Variance Reduced Optimization
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #73
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Associative Memory via a Sparse Recovery Model
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #75
Matrix Completion Under Monotonic Single Index Models
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #76
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #77
Convergence rates of sub-sampled Newton methods
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Variance Reduced Stochastic Gradient Descent with Neighbors
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #79
Non-convex Statistical Optimization for Sparse Tensor Graphical Model
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Convergence Rates of Active Learning for Maximum Likelihood Estimation
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #81
When are Kalman-Filter Restless Bandits Indexable?
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #82
Policy Gradient for Coherent Risk Measures
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #83
A Dual Augmented Block Minimization Framework for Learning with Limited Memory
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PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #84
On the Global Linear Convergence of Frank-Wolfe Optimization Variants
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #86
A Generalization of Submodular Cover via the Diminishing Return Property on the Integer Lattice
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #87
A Universal Catalyst for First-Order Optimization
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Fast and Memory Optimal Low-Rank Matrix Approximation
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #89
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #90
Linear Multi-Resource Allocation with Semi-Bandit Feedback
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Exactness of Approximate MAP Inference in Continuous MRFs
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #92
On the consistency theory of high dimensional variable screening
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #93
Finite-Time Analysis of Projected Langevin Monte Carlo
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #94
Optimal Testing for Properties of Distributions
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #96
Accelerated Mirror Descent in Continuous and Discrete Time
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #97
Information-theoretic lower bounds for convex optimization with erroneous oracles
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #98
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
[
PDF]
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs
[
PDF]
Oral
Thu Dec 10 06:50 AM -- 07:10 AM (PST) @ Room 210 A
Less is More: Nyström Computational Regularization
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Logarithmic Time Online Multiclass prediction
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Efficient and Parsimonious Agnostic Active Learning
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Matrix Completion with Noisy Side Information
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Scalable Semi-Supervised Aggregation of Classifiers
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Spherical Random Features for Polynomial Kernels
Spotlight
Thu Dec 10 07:10 AM -- 07:40 AM (PST) @ Room 210 A
Fast and Guaranteed Tensor Decomposition via Sketching
Break
Thu Dec 10 07:30 AM -- 09:00 AM (PST) @ 220 A
Breakfast
Session
Thu Dec 10 07:40 AM -- 07:50 AM (PST) @ 210 A
Closing Remarks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #1
Teaching Machines to Read and Comprehend
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #2
Saliency, Scale and Information: Towards a Unifying Theory
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #3
Semi-supervised Learning with Ladder Networks
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #4
Enforcing balance allows local supervised learning in spiking recurrent networks
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #7
Learning to Linearize Under Uncertainty
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #8
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #10
Convolutional Networks on Graphs for Learning Molecular Fingerprints
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #11
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #12
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #13
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #15
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #16
A Gaussian Process Model of Quasar Spectral Energy Distributions
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #17
Neural Adaptive Sequential Monte Carlo
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #18
Convolutional spike-triggered covariance analysis for neural subunit models
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #20
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #22
GP Kernels for Cross-Spectrum Analysis
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #23
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #24
Particle Gibbs for Infinite Hidden Markov Models
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #25
Sparse Local Embeddings for Extreme Multi-label Classification
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #26
Robust Spectral Inference for Joint Stochastic Matrix Factorization
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #28
A fast, universal algorithm to learn parametric nonlinear embeddings
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #29
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #30
Local Causal Discovery of Direct Causes and Effects
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #31
Discriminative Robust Transformation Learning
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #32
Max-Margin Majority Voting for Learning from Crowds
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #33
M-Best-Diverse Labelings for Submodular Energies and Beyond
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #34
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #35
Time-Sensitive Recommendation From Recurrent User Activities
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #36
Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #37
Logarithmic Time Online Multiclass prediction
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #38
Scalable Semi-Supervised Aggregation of Classifiers
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #39
Bounding the Cost of Search-Based Lifted Inference
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #40
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #41
Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #42
Sample Efficient Path Integral Control under Uncertainty
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #43
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #44
Parallelizing MCMC with Random Partition Trees
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #45
Fast Lifted MAP Inference via Partitioning
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #46
Active Learning from Weak and Strong Labelers
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #47
Fast and Guaranteed Tensor Decomposition via Sketching
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #48
Spherical Random Features for Polynomial Kernels
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #49
Learnability of Influence in Networks
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #50
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #51
Differentially private subspace clustering
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #52
Compressive spectral embedding: sidestepping the SVD
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #53
Generalization in Adaptive Data Analysis and Holdout Reuse
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #55
Matrix Completion with Noisy Side Information
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #56
A Market Framework for Eliciting Private Data
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #57
Optimal Ridge Detection using Coverage Risk
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #58
Fast Distributed k-Center Clustering with Outliers on Massive Data
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #59
Orthogonal NMF through Subspace Exploration
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #60
Fast Classification Rates for High-dimensional Gaussian Generative Models
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #61
Efficient and Parsimonious Agnostic Active Learning
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #62
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #63
Less is More: Nyström Computational Regularization
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #64
Predtron: A Family of Online Algorithms for General Prediction Problems
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #65
On the Optimality of Classifier Chain for Multi-label Classification
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #66
Smooth Interactive Submodular Set Cover
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #67
Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #68
Secure Multi-party Differential Privacy
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #69
Adaptive Stochastic Optimization: From Sets to Paths
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #70
Learning structured densities via infinite dimensional exponential families
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #71
Lifelong Learning with Non-i.i.d. Tasks
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #72
Learning with Symmetric Label Noise: The Importance of Being Unhinged
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #73
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #74
From random walks to distances on unweighted graphs
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #75
Robust Regression via Hard Thresholding
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #76
Column Selection via Adaptive Sampling
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #77
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #78
Optimal Linear Estimation under Unknown Nonlinear Transform
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #79
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #80
Learning with Incremental Iterative Regularization
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #81
No-Regret Learning in Bayesian Games
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #82
Sparse and Low-Rank Tensor Decomposition
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #83
Analysis of Robust PCA via Local Incoherence
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #84
Algorithmic Stability and Uniform Generalization
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #85
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #86
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #87
Unified View of Matrix Completion under General Structural Constraints
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #89
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #90
Online Learning for Adversaries with Memory: Price of Past Mistakes
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #91
Revenue Optimization against Strategic Buyers
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #92
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #93
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #94
Cornering Stationary and Restless Mixing Bandits with Remix-UCB
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #95
Fighting Bandits with a New Kind of Smoothness
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #96
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #97
The Pareto Regret Frontier for Bandits
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #98
Online Learning with Gaussian Payoffs and Side Observations
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #99
Fast Rates for Exp-concave Empirical Risk Minimization
[
PDF]
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #100
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models
[
PDF]
Break
Thu Dec 10 10:50 AM -- 11:30 AM (PST) @ 210 A
Coffee Break
Symposium
Thu Dec 10 12:00 PM -- 06:00 PM (PST) @ 210 a,b Level 2
Deep Learning Symposium
[
Alex Graves]
[
David Sontag]
[
Emily Denton]
[
Harri Valpola]
[
Leon Gatys]
[
Max Jaderberg]
[
Panel]
[
Panel Discussion]
[
Pieter Abbeel]
[
Sergey Ioffe]
[
Trevor Darrell]
[
Welcome]
[
Xiaogang Wang]
Symposium
Thu Dec 10 12:00 PM -- 06:00 PM (PST) @ Level 5 Room 510 BD
Brains, Minds and Machines
[
Andrew Saxe]
[
Christof Koch]
[
Demis Hassabis]
[
Gabriel Kreiman]
[
Joshua Tenenbaum]
[
Panel Discussion]
[
Surya Ganguli]
[
Tomaso Poggio]
Symposium
Thu Dec 10 12:00 PM -- 06:00 PM (PST) @ 210 e, f Level 2
Algorithms Among Us: the Societal Impacts of Machine Learning
Break
Thu Dec 10 04:15 PM -- 04:45 PM (PST)
Coffee Break
Break
Thu Dec 10 06:00 PM -- 07:00 PM (PST) @ 220A
Hors d'oeuvres
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 d
Learning Faster from Easy Data II
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 512 cg
Cognitive Computation: Integrating neural and symbolic approaches
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 513 ef
The 1st International Workshop "Feature Extraction: Modern Questions and Challenges"
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ Room 515 a
Machine Learning and Interpretation in Neuroimaging (day 1)
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 515 bc
Applying (machine) Learning to Experimental Physics (ALEPH) and «Flavours of Physics» challenge
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 c
Nonparametric Methods for Large Scale Representation Learning
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 513 ab
Advances in Approximate Bayesian Inference
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 510 ac
Optimization for Machine Learning (OPT2015)
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 514 bc
Time Series Workshop
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 e
Modelling and inference for dynamics on complex interaction networks: joining up machine learning and statistical physics
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 513 cd
Deep Reinforcement Learning
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 514 a
Adaptive Data Analysis
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 512 e
Machine Learning for (e-)Commerce
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 a
ABC in Montreal
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 b
Machine Learning for Spoken Language Understanding and Interactions
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 511 f
Statistical Methods for Understanding Neural Systems
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 510 bd
Machine Learning For Healthcare (MLHC)
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 512 dh
Multimodal Machine Learning
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 512 bf
Bounded Optimality and Rational Metareasoning
Workshop
Fri Dec 11 05:30 AM -- 03:30 PM (PST) @ 512 a
Probabilistic Integration
Break
Fri Dec 11 07:30 AM -- 09:00 AM (PST) @ 220 A
Breakfast
Break
Fri Dec 11 10:00 AM -- 10:30 AM (PST) @ Foyer - 5th floor
Coffee Break
Break
Fri Dec 11 04:00 PM -- 04:30 PM (PST) @ Foyer - 5th floor
Coffee Break
Workshop
Sat Dec 12 05:00 AM -- 03:30 PM (PST) @ 511 f
Extreme Classification 2015: Multi-class and Multi-label Learning in Extremely Large Label Spaces
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 c
Multiresolution methods for large-scale learning
[
Youtube Video - Bach]
[
Youtube Video - Benson]
[
Youtube Video - Garcke]
[
Youtube Video - Kondor]
[
Youtube Video - Mahoney]
[
Youtube Video - March]
[
Youtube Video - Mukherjee]
[
Youtube Video - O'Neil]
[
Youtube Video - Safro]
[
Youtube Video - Sibony]
[
Youtube Video - Srivastava]
[
Youtube Video - Vandergheynst]
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 a
Learning, Inference and Control of Multi-Agent Systems
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 512 dh
Learning and privacy with incomplete data and weak supervision
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 510 ac
Reasoning, Attention, Memory (RAM) Workshop
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 512 e
Challenges in Machine Learning (CiML 2015): "Open Innovation" and "Coopetitions"
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 514 a
Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 510 bd
Machine Learning in Computational Biology
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 b
Bayesian Optimization: Scalability and Flexibility
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 513 ef
Black box learning and inference
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 e
BigNeuro 2015: Making sense of big neural data
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 514 bc
Transfer and Multi-Task Learning: Trends and New Perspectives
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 512 cg
Cognitive Computation: Integrating neural and symbolic approaches (day 2)
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 515 bc
Bayesian Nonparametrics: The Next Generation
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ Room 515 a
Machine Learning and Interpretation in Neuroimaging (day 2)
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 512 bf
Networks in the Social and Information Sciences
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 d
Machine Learning Systems
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 513 ab
Scalable Monte Carlo Methods for Bayesian Analysis of Big Data
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 512 a
Quantum Machine Learning
Workshop
Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 513 cd
Non-convex Optimization for Machine Learning: Theory and Practice
Break
Sat Dec 12 07:30 AM -- 09:00 AM (PST) @ 220 A
Breakfast
Break
Sat Dec 12 10:00 AM -- 10:30 AM (PST) @ Foyer - 5th floor
Coffee Break
Break
Sat Dec 12 04:00 PM -- 04:30 PM (PST) @ Foyer - 5th floor
Coffee Break
Break
Sat Dec 12 07:00 PM -- 11:00 PM (PST) @ 210
Banquet