NeurIPS 2015

403 papers

Regret-Based Pruning in Extensive-Form Games

Noam Brown, Tuomas Sandholm

Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution

Yan Huang, Wei Wang, Liang Wang

Robust PCA with compressed data

Wooseok Ha, Rina Foygel Barber

Distributed Submodular Cover: Succinctly Summarizing Massive Data

Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause

A Universal Catalyst for First-Order Optimization

Hongzhou Lin, Julien Mairal, Zaïd Harchaoui

Finite-Time Analysis of Projected Langevin Monte Carlo

Sébastien Bubeck, Ronen Eldan, Joseph Lehec

Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction

Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama

On the Global Linear Convergence of Frank-Wolfe Optimization Variants

Simon Lacoste-Julien, Martin Jaggi

Fast, Provable Algorithms for Isotonic Regression in all L_p-norms

Rasmus Kyng, Anup Rao, Sushant Sachdeva

Variational Dropout and the Local Reparameterization Trick

Diederik P. Kingma, Tim Salimans, Max Welling

Tractable Learning for Complex Probability Queries

Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck

Generalization in Adaptive Data Analysis and Holdout Reuse

Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toni Pitassi, Omer Reingold

Deep Knowledge Tracing

Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami

Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees

François-Xavier Briol, Chris Oates, Mark Girolami, Michael A Osborne

Submodular Hamming Metrics

Jennifer A Gillenwater, Rishabh K Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes

Learning to Transduce with Unbounded Memory

Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil Blunsom

Learning Causal Graphs with Small Interventions

Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G Dimakis, Sriram Vishwanath

Unsupervised Learning by Program Synthesis

Kevin Ellis, Armando Solar-Lezama, Josh Tenenbaum

A Recurrent Latent Variable Model for Sequential Data

Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville

Fast Two-Sample Testing with Analytic Representations of Probability Measures

Kacper P Chwialkowski, Aaditya Ramdas, Dino Sejdinovic, Arthur Gretton

Parallel Correlation Clustering on Big Graphs

Xinghao Pan, Dimitris Papailiopoulos, Samet Oymak, Benjamin Recht, Kannan Ramchandran

Subset Selection by Pareto Optimization

Chao Qian, Yang Yu, Zhi-Hua Zhou

Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization

Niao He, Zaïd Harchaoui

A Reduced-Dimension fMRI Shared Response Model

Po-Hsuan (Cameron) Chen, Janice Chen, Yaara Yeshurun, Uri Hasson, James Haxby

Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width

Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Re

Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks

Kevin Scaman, Remi Lemonnier, Nicolas Vayatis

Alternating Minimization for Regression Problems with Vector-valued Outputs

Prateek Jain, Ambuj Tewari

Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring

David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass

Teaching Machines to Read and Comprehend

Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

Changyou Chen, Nan Ding, Lawrence Carin

Bayesian dark knowledge

Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling

Learning both Weights and Connections for Efficient Neural Network

Song Han, Jeff Pool, John Tran, William Dally

Fast Rates for Exp-concave Empirical Risk Minimization

Tomer Koren, Kfir Levy

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding

Rie Johnson, Tong Zhang

Black-box optimization of noisy functions with unknown smoothness

Jean-Bastien Grill, Michal Valko, Rémi Munos

On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs

Wei Cao, Jian Li, Yufei Tao, Zhize Li

Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach

Wenye Li

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

Emily L Denton, Soumith Chintala, arthur szlam, Rob Fergus

Learning with a Wasserstein Loss

Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya, Tomaso A Poggio

Large-scale probabilistic predictors with and without guarantees of validity

Vladimir Vovk, Ivan Petej, Valentina Fedorova

Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation

Alaa Saade, Florent Krzakala, Lenka Zdeborová

Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks

Minhyung Cho, Chandra Dhir, Jaehyung Lee

Texture Synthesis Using Convolutional Neural Networks

Leon Gatys, Alexander S Ecker, Matthias Bethge

Efficient Output Kernel Learning for Multiple Tasks

Pratik Kumar Jawanpuria, Maksim Lapin, Matthias Hein, Bernt Schiele

Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression

Yu-Ying Liu, Shuang Li, Fuxin Li, Le Song, James M. Rehg

Saliency, Scale and Information: Towards a Unifying Theory

Shafin Rahman, Neil Bruce

StopWasting My Gradients: Practical SVRG

Reza Babanezhad Harikandeh, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konečný

Basis refinement strategies for linear value function approximation in MDPs

Gheorghe Comanici, Doina Precup, Prakash Panangaden

Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference

Ted Meeds, Max Welling

Is Approval Voting Optimal Given Approval Votes?

Ariel D Procaccia, Nisarg Shah

Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma

Murat A Erdogdu

Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

Manuel Watter, Jost Springenberg, Joschka Boedecker, Martin Riedmiller

Secure Multi-party Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

Expectation Particle Belief Propagation

Thibaut Lienart, Yee Whye Teh, Arnaud Doucet

Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability

Xia Qu, Prashant Doshi

Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling

Ming Liang, Xiaolin Hu, Bo Zhang

Max-Margin Deep Generative Models

Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang

Rethinking LDA: Moment Matching for Discrete ICA

Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien

Segregated Graphs and Marginals of Chain Graph Models

Ilya Shpitser

A Complete Recipe for Stochastic Gradient MCMC

Tianqi Chen, Emily B. Fox, Yian Ma, Yi-An Ma

Supervised Learning for Dynamical System Learning

Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon

Neural Adaptive Sequential Monte Carlo

Shixiang (Shane) Gu, Zoubin Ghahramani, Richard E Turner

High-dimensional neural spike train analysis with generalized count linear dynamical systems

Yuanjun Gao, Lars Busing, Krishna V. Shenoy, John P. Cunningham

Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms

Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Re

Copeland Dueling Bandits

Masrour Zoghi, Zohar S Karnin, Shimon Whiteson, Maarten de Rijke

Sample Complexity Bounds for Iterative Stochastic Policy Optimization

Marin Kobilarov

Color Constancy by Learning to Predict Chromaticity from Luminance

Ayan Chakrabarti

Community Detection via Measure Space Embedding

Mark Kozdoba, Shie Mannor

Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems

Ruoyu Sun, Mingyi Hong

Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels

Felipe Tobar, Thang D Bui, Richard E Turner

Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's

Vitaly Feldman, Will Perkins, Santosh Vempala

Deep Temporal Sigmoid Belief Networks for Sequence Modeling

Zhe Gan, Chunyuan Li, Ricardo Henao, David E Carlson, Lawrence Carin

Learning From Small Samples: An Analysis of Simple Decision Heuristics

Ozgur Simsek, Marcus Buckmann

Beyond Convexity: Stochastic Quasi-Convex Optimization

Elad Hazan, Kfir Levy, Shai Shalev-shwartz

Regularized EM Algorithms: A Unified Framework and Statistical Guarantees

Xinyang Yi, Constantine Caramanis

Lifelong Learning with Non-i.i.d. Tasks

Anastasia Pentina, Christoph H. Lampert

BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions

Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen

Fast Distributed k-Center Clustering with Outliers on Massive Data

Gustavo Malkomes, Matt J Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley

End-To-End Memory Networks

Sainbayar Sukhbaatar, arthur szlam, Jason Weston, Rob Fergus

Learning visual biases from human imagination

Carl Vondrick, Hamed Pirsiavash, Aude Oliva, Antonio Torralba

Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices

Martin Slawski, Ping Li, Matthias Hein

Approximating Sparse PCA from Incomplete Data

ABHISEK KUNDU, Petros Drineas, Malik Magdon-Ismail

Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families

Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltan Szabo, Arthur Gretton

Online Learning with Gaussian Payoffs and Side Observations

Yifan Wu, András György, Csaba Szepesvári

Estimating Mixture Models via Mixtures of Polynomials

Sida Wang, Arun Tejasvi Chaganty, Percy Liang

Learning Structured Output Representation using Deep Conditional Generative Models

Kihyuk Sohn, Honglak Lee, Xinchen Yan

A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA

James R Voss, Mikhail Belkin, Luis Rademacher

NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning

Kevin G. Jamieson, Lalit Jain, Chris Fernandez, Nicholas J. Glattard, Rob Nowak

Hidden Technical Debt in Machine Learning Systems

D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips

A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks

Cengiz Pehlevan, Dmitri Chklovskii

Consistent Multilabel Classification

Oluwasanmi O Koyejo, Nagarajan Natarajan, Pradeep K Ravikumar, Inderjit S Dhillon

On the Optimality of Classifier Chain for Multi-label Classification

Weiwei Liu, Ivor Tsang

Linear Multi-Resource Allocation with Semi-Bandit Feedback

Tor Lattimore, Koby Crammer, Csaba Szepesvári

Structured Transforms for Small-Footprint Deep Learning

Vikas Sindhwani, Tara Sainath, Sanjiv Kumar

Efficient Thompson Sampling for Online Matrix-Factorization Recommendation

Jaya Kawale, Hung H Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla

An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching

Xiao Li, Kannan Ramchandran

Principal Differences Analysis: Interpretable Characterization of Differences between Distributions

Jonas W Mueller, Tommi Jaakkola

Streaming Min-max Hypergraph Partitioning

Dan Alistarh, Jennifer Iglesias, Milan Vojnovic

Learning structured densities via infinite dimensional exponential families

Siqi Sun, Mladen Kolar, Jinbo Xu

Exploring Models and Data for Image Question Answering

Mengye Ren, Ryan Kiros, Richard Zemel