(403 events)
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Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #1
Texture Synthesis Using Convolutional Neural Networks
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #3
Grammar as a Foreign Language
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Generative Image Modeling Using Spatial LSTMs
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #7
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #8
Exploring Models and Data for Image Question Answering
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
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #11
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #12
3D Object Proposals for Accurate Object Class Detection
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #13
The Poisson Gamma Belief Network
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #15
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #16
Learning to Transduce with Unbounded Memory
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #17
Spectral Representations for Convolutional Neural Networks
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #18
A Theory of Decision Making Under Dynamic Context
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #19
Bidirectional Recurrent Neural Networks as Generative Models
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #20
Recognizing retinal ganglion cells in the dark
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #21
A Recurrent Latent Variable Model for Sequential Data
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #22
Deep Knowledge Tracing
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #23
Deep Temporal Sigmoid Belief Networks for Sequence Modeling
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #24
Hidden Technical Debt in Machine Learning Systems
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Statistical Model Criticism using Kernel Two Sample Tests
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #26
Calibrated Structured Prediction
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #27
A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #29
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #30
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Learning spatiotemporal trajectories from manifold-valued longitudinal data
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Variational Dropout and the Local Reparameterization Trick
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #35
Infinite Factorial Dynamical Model
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #36
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #37
Copula variational inference
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Fast Second Order Stochastic Backpropagation for Variational Inference
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #39
Rethinking LDA: Moment Matching for Discrete ICA
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Model-Based Relative Entropy Stochastic Search
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #41
Supervised Learning for Dynamical System Learning
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Expectation Particle Belief Propagation
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Embedding Inference for Structured Multilabel Prediction
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Tractable Learning for Complex Probability Queries
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #46
Local Expectation Gradients for Black Box Variational Inference
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #47
Learning with a Wasserstein Loss
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Fast and Accurate Inference of Plackett–Luce Models
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #50
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Learning with Relaxed Supervision
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #52
M-Statistic for Kernel Change-Point Detection
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #53
Fast Two-Sample Testing with Analytic Representations of Probability Measures
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Adversarial Prediction Games for Multivariate Losses
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #55
Regressive Virtual Metric Learning
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Halting in Random Walk Kernels
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #57
Rate-Agnostic (Causal) Structure Learning
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Online Prediction at the Limit of Zero Temperature
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #59
Lifted Symmetry Detection and Breaking for MAP Inference
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Bandits with Unobserved Confounders: A Causal Approach
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #61
Sample Complexity Bounds for Iterative Stochastic Policy Optimization
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #62
Basis refinement strategies for linear value function approximation in MDPs
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #63
Probabilistic Variational Bounds for Graphical Models
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
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Discrete Rényi Classifiers
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Decomposition Bounds for Marginal MAP
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Estimating Mixture Models via Mixtures of Polynomials
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #71
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #73
Robust PCA with compressed data
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #75
Subspace Clustering with Irrelevant Features via Robust Dantzig Selector
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #76
A class of network models recoverable by spectral clustering
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #77
Monotone k-Submodular Function Maximization with Size Constraints
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Smooth and Strong: MAP Inference with Linear Convergence
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #79
StopWasting My Gradients: Practical SVRG
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #81
Differentially Private Learning of Structured Discrete Distributions
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #82
Robust Portfolio Optimization
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #83
Bayesian Optimization with Exponential Convergence
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #84
Fast Randomized Kernel Ridge Regression with Statistical Guarantees
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms
Poster
Mon Dec 07 04:00 PM (PST) @ 210 C #86
Beyond Convexity: Stochastic Quasi-Convex Optimization
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #89
Black-box optimization of noisy functions with unknown smoothness
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #90
Combinatorial Cascading Bandits
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #92
Sum-of-Squares Lower Bounds for Sparse PCA
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #93
Online Gradient Boosting
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Convergence Analysis of Prediction Markets via Randomized Subspace Descent
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #96
Accelerated Proximal Gradient Methods for Nonconvex Programming
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #97
Nearly Optimal Private LASSO
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #98
Minimax Time Series Prediction
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Communication Complexity of Distributed Convex Learning and Optimization
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
Poster
Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #101
A Nonconvex Optimization Framework for Low Rank Matrix Estimation
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #2
Shepard Convolutional Neural Networks
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #3
Learning Structured Output Representation using Deep Conditional Generative Models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #4
Expressing an Image Stream with a Sequence of Natural Sentences
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Visalogy: Answering Visual Analogy Questions
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #6
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #9
Learning visual biases from human imagination
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #10
Character-level Convolutional Networks for Text Classification
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #11
Winner-Take-All Autoencoders
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #12
Learning both Weights and Connections for Efficient Neural Network
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #13
Interactive Control of Diverse Complex Characters with Neural Networks
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Biologically Inspired Dynamic Textures for Probing Motion Perception
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #15
Unsupervised Learning by Program Synthesis
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #16
Deep Poisson Factor Modeling
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #18
Tensorizing Neural Networks
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #21
Unlocking neural population non-stationarities using hierarchical dynamics models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #22
Deeply Learning the Messages in Message Passing Inference
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Latent Bayesian melding for integrating individual and population models
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #28
The Population Posterior and Bayesian Modeling on Streams
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #29
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #30
Preconditioned Spectral Descent for Deep Learning
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Learning Continuous Control Policies by Stochastic Value Gradients
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Automatic Variational Inference in Stan
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #35
Data Generation as Sequential Decision Making
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #36
Stochastic Expectation Propagation
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #37
Deep learning with Elastic Averaging SGD
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Learning with Group Invariant Features: A Kernel Perspective.
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Probabilistic Line Searches for Stochastic Optimization
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #41
A hybrid sampler for Poisson-Kingman mixture models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Reflection, Refraction, and Hamiltonian Monte Carlo
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Planar Ultrametrics for Image Segmentation
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Learning Bayesian Networks with Thousands of Variables
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
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Large-scale probabilistic predictors with and without guarantees of validity
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #50
On the Accuracy of Self-Normalized Log-Linear Models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Policy Evaluation Using the Ω-Return
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #52
Community Detection via Measure Space Embedding
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Inference for determinantal point processes without spectral knowledge
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #55
Sample Complexity of Learning Mahalanobis Distance Metrics
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Matrix Manifold Optimization for Gaussian Mixtures
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #57
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #59
The Self-Normalized Estimator for Counterfactual Learning
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Distributionally Robust Logistic Regression
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #61
Top-k Multiclass SVM
Poster
Tue Dec 08 04:00 PM (PST) @ 210 C #62
Measuring Sample Quality with Stein's Method
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #63
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #65
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Parallel Correlation Clustering on Big Graphs
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #67
Fast Bidirectional Probability Estimation in Markov Models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Evaluating the statistical significance of biclusters
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #69
Regularization Path of Cross-Validation Error Lower Bounds
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Sampling from Probabilistic Submodular Models
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #71
Submodular Hamming Metrics
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Extending Gossip Algorithms to Distributed Estimation of U-statistics
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Collaboratively Learning Preferences from Ordinal Data
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #76
Alternating Minimization for Regression Problems with Vector-valued Outputs
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Subset Selection by Pareto Optimization
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Minimum Weight Perfect Matching via Blossom Belief Propagation
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #81
b-bit Marginal Regression
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
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #84
On the Pseudo-Dimension of Nearly Optimal Auctions
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Closed-form Estimators for High-dimensional Generalized Linear Models
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #87
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Competitive Distribution Estimation: Why is Good-Turing Good
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #89
A Universal Primal-Dual Convex Optimization Framework
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #90
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Private Graphon Estimation for Sparse Graphs
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #92
HONOR: Hybrid Optimization for NOn-convex Regularized problems
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
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #94
Super-Resolution Off the Grid
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Optimal Rates for Random Fourier Features
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #96
Combinatorial Bandits Revisited
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #97
Fast Convergence of Regularized Learning in Games
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #98
On Elicitation Complexity
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Online Learning with Adversarial Delays
Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #100
Structured Estimation with Atomic Norms: General Bounds and Applications
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #1
Deep Visual Analogy-Making
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #2
Where are they looking?
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #3
Spatial Transformer Networks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #4
Training Very Deep Networks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #5
Attention-Based Models for Speech Recognition
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #6
Deep Convolutional Inverse Graphics Network
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #7
End-To-End Memory Networks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #8
Learning to Segment Object Candidates
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #9
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
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
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
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #13
Backpropagation for Energy-Efficient Neuromorphic Computing
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #14
Learning Wake-Sleep Recurrent Attention Models
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #15
On-the-Job Learning with Bayesian Decision Theory
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #16
Color Constancy by Learning to Predict Chromaticity from Luminance
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #17
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #18
Action-Conditional Video Prediction using Deep Networks in Atari Games
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #19
Bayesian Active Model Selection with an Application to Automated Audiometry
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #20
Efficient and Robust Automated Machine Learning
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #23
A Reduced-Dimension fMRI Shared Response Model
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #25
Precision-Recall-Gain Curves: PR Analysis Done Right
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #27
Equilibrated adaptive learning rates for non-convex optimization
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #29
Gaussian Process Random Fields
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #30
MCMC for Variationally Sparse Gaussian Processes
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #31
Streaming, Distributed Variational Inference for Bayesian Nonparametrics
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #32
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #33
Human Memory Search as Initial-Visit Emitting Random Walk
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #34
Structured Transforms for Small-Footprint Deep Learning
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #35
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #36
A Structural Smoothing Framework For Robust Graph Comparison
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #37
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #38
Inverse Reinforcement Learning with Locally Consistent Reward Functions
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #39
Consistent Multilabel Classification
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #40
Is Approval Voting Optimal Given Approval Votes?
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #41
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Efficient Non-greedy Optimization of Decision Trees
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Statistical Topological Data Analysis - A Kernel Perspective
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Variational Consensus Monte Carlo
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Softstar: Heuristic-Guided Probabilistic Inference
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #46
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #47
A Complete Recipe for Stochastic Gradient MCMC
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #48
Barrier Frank-Wolfe for Marginal Inference
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Practical and Optimal LSH for Angular Distance
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #50
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Kullback-Leibler Proximal Variational Inference
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #52
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #53
Streaming Min-max Hypergraph Partitioning
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Efficient Output Kernel Learning for Multiple Tasks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #55
Gradient Estimation Using Stochastic Computation Graphs
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Lifted Inference Rules With Constraints
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #57
Sparse PCA via Bipartite Matchings
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #58
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #61
Segregated Graphs and Marginals of Chain Graph Models
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #62
Approximating Sparse PCA from Incomplete Data
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
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
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Testing Closeness With Unequal Sized Samples
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #67
Learning Causal Graphs with Small Interventions
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Regret-Based Pruning in Extensive-Form Games
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #69
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Bounding errors of Expectation-Propagation
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Local Smoothness in Variance Reduced Optimization
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #73
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Associative Memory via a Sparse Recovery Model
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #75
Matrix Completion Under Monotonic Single Index Models
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #76
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #77
Convergence rates of sub-sampled Newton methods
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Variance Reduced Stochastic Gradient Descent with Neighbors
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #79
Non-convex Statistical Optimization for Sparse Tensor Graphical Model
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #81
When are Kalman-Filter Restless Bandits Indexable?
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #82
Policy Gradient for Coherent Risk Measures
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #84
On the Global Linear Convergence of Frank-Wolfe Optimization Variants
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #85
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #87
A Universal Catalyst for First-Order Optimization
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #88
Fast and Memory Optimal Low-Rank Matrix Approximation
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #89
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #90
Linear Multi-Resource Allocation with Semi-Bandit Feedback
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Exactness of Approximate MAP Inference in Continuous MRFs
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #92
On the consistency theory of high dimensional variable screening
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #93
Finite-Time Analysis of Projected Langevin Monte Carlo
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #94
Optimal Testing for Properties of Distributions
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #96
Accelerated Mirror Descent in Continuous and Discrete Time
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #97
Information-theoretic lower bounds for convex optimization with erroneous oracles
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #98
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
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
Poster
Wed Dec 09 04:00 PM -- 08:59 PM (PST) @ 210 C #100
Adaptive Online Learning
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #1
Teaching Machines to Read and Comprehend
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #2
Saliency, Scale and Information: Towards a Unifying Theory
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #3
Semi-supervised Learning with Ladder Networks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #4
Enforcing balance allows local supervised learning in spiking recurrent networks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #5
Semi-supervised Sequence Learning
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #6
Skip-Thought Vectors
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #7
Learning to Linearize Under Uncertainty
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #9
Natural Neural Networks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #10
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #11
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #12
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #14
Max-Margin Deep Generative Models
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #16
A Gaussian Process Model of Quasar Spectral Energy Distributions
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #17
Neural Adaptive Sequential Monte Carlo
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #18
Convolutional spike-triggered covariance analysis for neural subunit models
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #19
Rectified Factor Networks
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #21
Bayesian dark knowledge
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #22
GP Kernels for Cross-Spectrum Analysis
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #24
Particle Gibbs for Infinite Hidden Markov Models
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #25
Sparse Local Embeddings for Extreme Multi-label Classification
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #26
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #27
Space-Time Local Embeddings
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #28
A fast, universal algorithm to learn parametric nonlinear embeddings
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)
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #30
Local Causal Discovery of Direct Causes and Effects
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #31
Discriminative Robust Transformation Learning
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #32
Max-Margin Majority Voting for Learning from Crowds
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #33
M-Best-Diverse Labelings for Submodular Energies and Beyond
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #34
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #35
Time-Sensitive Recommendation From Recurrent User Activities
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #37
Logarithmic Time Online Multiclass prediction
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #38
Scalable Semi-Supervised Aggregation of Classifiers
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #39
Bounding the Cost of Search-Based Lifted Inference
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #40
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #41
Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #42
Sample Efficient Path Integral Control under Uncertainty
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #43
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #44
Parallelizing MCMC with Random Partition Trees
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #45
Fast Lifted MAP Inference via Partitioning
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #46
Active Learning from Weak and Strong Labelers
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #47
Fast and Guaranteed Tensor Decomposition via Sketching
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #48
Spherical Random Features for Polynomial Kernels
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #49
Learnability of Influence in Networks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #50
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #51
Differentially private subspace clustering
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #52
Compressive spectral embedding: sidestepping the SVD
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #53
Generalization in Adaptive Data Analysis and Holdout Reuse
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #54
Online F-Measure Optimization
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #55
Matrix Completion with Noisy Side Information
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #56
A Market Framework for Eliciting Private Data
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #57
Optimal Ridge Detection using Coverage Risk
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #58
Fast Distributed k-Center Clustering with Outliers on Massive Data
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #59
Orthogonal NMF through Subspace Exploration
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #60
Fast Classification Rates for High-dimensional Gaussian Generative Models
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #61
Efficient and Parsimonious Agnostic Active Learning
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #62
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #63
Less is More: Nyström Computational Regularization
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #64
Predtron: A Family of Online Algorithms for General Prediction Problems
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #65
On the Optimality of Classifier Chain for Multi-label Classification
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #66
Smooth Interactive Submodular Set Cover
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #67
Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #68
Secure Multi-party Differential Privacy
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #69
Adaptive Stochastic Optimization: From Sets to Paths
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #70
Learning structured densities via infinite dimensional exponential families
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #71
Lifelong Learning with Non-i.i.d. Tasks
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #72
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #73
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #74
From random walks to distances on unweighted graphs
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #75
Robust Regression via Hard Thresholding
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #76
Column Selection via Adaptive Sampling
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #78
Optimal Linear Estimation under Unknown Nonlinear Transform
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #79
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #80
Learning with Incremental Iterative Regularization
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #81
No-Regret Learning in Bayesian Games
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #82
Sparse and Low-Rank Tensor Decomposition
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #83
Analysis of Robust PCA via Local Incoherence
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #84
Algorithmic Stability and Uniform Generalization
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #86
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #87
Unified View of Matrix Completion under General Structural Constraints
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #88
Copeland Dueling Bandits
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #90
Online Learning for Adversaries with Memory: Price of Past Mistakes
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #91
Revenue Optimization against Strategic Buyers
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
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #94
Cornering Stationary and Restless Mixing Bandits with Remix-UCB
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #95
Fighting Bandits with a New Kind of Smoothness
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
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #97
The Pareto Regret Frontier for Bandits
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #98
Online Learning with Gaussian Payoffs and Side Observations
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #99
Fast Rates for Exp-concave Empirical Risk Minimization
Poster
Thu Dec 10 08:00 AM -- 12:00 PM (PST) @ 210 C #100
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models