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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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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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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #41
A hybrid sampler for Poisson-Kingman mixture models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #42
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #43
Reflection, Refraction, and Hamiltonian Monte Carlo
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #44
Planar Ultrametrics for Image Segmentation
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #45
Learning Bayesian Networks with Thousands of Variables
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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
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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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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
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #49
Large-scale probabilistic predictors with and without guarantees of validity
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #51
Policy Evaluation Using the Ω-Return
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #52
Community Detection via Measure Space Embedding
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #54
Inference for determinantal point processes without spectral knowledge
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #56
Matrix Manifold Optimization for Gaussian Mixtures
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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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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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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #60
Distributionally Robust Logistic Regression
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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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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
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #66
Parallel Correlation Clustering on Big Graphs
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #67
Fast Bidirectional Probability Estimation in Markov Models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #68
Evaluating the statistical significance of biclusters
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #70
Sampling from Probabilistic Submodular Models
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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #72
Extending Gossip Algorithms to Distributed Estimation of U-statistics
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #74
Collaboratively Learning Preferences from Ordinal Data
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #76
Alternating Minimization for Regression Problems with Vector-valued Outputs
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #78
Subset Selection by Pareto Optimization
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #80
Minimum Weight Perfect Matching via Blossom Belief Propagation
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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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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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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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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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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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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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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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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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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #91
Private Graphon Estimation for Sparse Graphs
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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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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #95
Optimal Rates for Random Fourier Features
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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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Poster
Tue Dec 08 04:00 PM -- 08:59 PM (PST) @ 210 C #99
Online Learning with Adversarial Delays
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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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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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