NeurIPS 2016

569 papers

Guided Policy Search via Approximate Mirror Descent

William H Montgomery, Sergey Levine

Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint

Nguyen Cuong, Huan Xu

Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale

Firas Abuzaid, Joseph K. Bradley, Feynman T Liang, Andrew Feng, Lee Yang

Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy

Aryan Mokhtari, Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann, Alejandro Ribeiro

High-Rank Matrix Completion and Clustering under Self-Expressive Models

Ehsan Elhamifar

Using Fast Weights to Attend to the Recent Past

Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu

A state-space model of cross-region dynamic connectivity in MEG/EEG

Ying Yang, Elissa Aminoff, Michael Tarr, Robert E Kass

Double Thompson Sampling for Dueling Bandits

Huasen Wu, Xin Liu

Hierarchical Question-Image Co-Attention for Visual Question Answering

Jiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh

Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes

Hassan A Kingravi, Harshal R Maske, Girish Chowdhary

Learning User Perceived Clusters with Feature-Level Supervision

Ting-Yu Cheng, Guiguan Lin, xinyang gong, Kang-Jun Liu, Shan-Hung (Brandon) Wu

A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification

Steven Cheng-Xian Li, Benjamin M. Marlin

On Regularizing Rademacher Observation Losses

Richard Nock

Variance Reduction in Stochastic Gradient Langevin Dynamics

Kumar Avinava Dubey, Sashank J. Reddi, Sinead A Williamson, Barnabás Póczos, Alexander J Smola

Multimodal Residual Learning for Visual QA

Jin-Hwa Kim, Sang-Woo Lee, Donghyun Kwak, Min-Oh Heo, Jeonghee Kim

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes

Matteo Turchetta, Felix Berkenkamp, Andreas Krause

Safe Policy Improvement by Minimizing Robust Baseline Regret

Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow

Distributed Flexible Nonlinear Tensor Factorization

Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu

Review Networks for Caption Generation

Zhilin Yang, Ye Yuan, Yuexin Wu, William W. Cohen, Ruslan Salakhutdinov

Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease

Hao Zhou, Vamsi K Ithapu, Sathya Narayanan Ravi, Vikas Singh, Grace Wahba

Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds

Hongyi Zhang, Sashank J. Reddi, Suvrit Sra

Adaptive Skills Adaptive Partitions (ASAP)

Daniel J Mankowitz, Timothy A Mann, Shie Mannor

The Power of Adaptivity in Identifying Statistical Alternatives

Kevin G. Jamieson, Daniel Haas, Benjamin Recht

Measuring Neural Net Robustness with Constraints

Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori

Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making

Himabindu Lakkaraju, Jure Leskovec

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization

Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Threshold Learning for Optimal Decision Making

Nathan F. Lepora, Nathan F Lepora

Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates

Yuanzhi Li, Yingyu Liang, Andrej Risteski

Deconvolving Feedback Loops in Recommender Systems

Ayan Sinha, David F Gleich, Karthik Ramani

Clustering with Same-Cluster Queries

Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David

The Limits of Learning with Missing Data

Brian Bullins, Elad Hazan, Tomer Koren

Variational Inference in Mixed Probabilistic Submodular Models

Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

Accelerating Stochastic Composition Optimization

Mengdi Wang, Ji Liu, Ethan Fang

Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

Rong Zhu

Matching Networks for One Shot Learning

Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, Daan Wierstra

What Makes Objects Similar: A Unified Multi-Metric Learning Approach

Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang, Zhi-Hua Zhou

Cooperative Graphical Models

Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause

A Multi-Batch L-BFGS Method for Machine Learning

Albert S Berahas, Jorge Nocedal, Martin Takac

Structured Sparse Regression via Greedy Hard Thresholding

Prateek Jain, Nikhil Rao, Inderjit S Dhillon

Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods

Cristina Savin, Gasper Tkacik

Deep Exploration via Bootstrapped DQN

Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy

A Credit Assignment Compiler for Joint Prediction

Kai-Wei Chang, He He, Stephane Ross, Hal Daume III, John Langford

Infinite Hidden Semi-Markov Modulated Interaction Point Process

matt zhang, Peng Lin, Ting Guo, Yang Wang, Fang Chen

Nested Mini-Batch K-Means

James Newling, Francois Fleuret

Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back

Vitaly Feldman

Estimating the Size of a Large Network and its Communities from a Random Sample

Lin Chen, Amin Karbasi, Forrest W. Crawford

Dynamic Filter Networks

Xu Jia, Bert De Brabandere, Tinne Tuytelaars, Luc V Gool, Luc V. Gool

Near-Optimal Smoothing of Structured Conditional Probability Matrices

Moein Falahatgar, Mesrob I Ohannessian, Alon Orlitsky

On Mixtures of Markov Chains

Rishi Gupta, Ravi Kumar, Sergei Vassilvitskii

Coordinate-wise Power Method

Qi Lei, Kai Zhong, Inderjit S Dhillon

Improved Techniques for Training GANs

Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford

Fast recovery from a union of subspaces

Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

A Consistent Regularization Approach for Structured Prediction

Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

“Congruent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation

He Wang, K. Y. Michael Wong, Si Wu, Wenhao Zhang, Wen-Hao Zhang

Preference Completion from Partial Rankings

Suriya Gunasekar, Oluwasanmi O Koyejo, Joydeep Ghosh

Community Detection on Evolving Graphs

Aris Anagnostopoulos, Jakub Łącki, Silvio Lattanzi, Stefano Leonardi, Mohammad Mahdian

Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models

Marc Vuffray, Sidhant Misra, Andrey Lokhov, Michael Chertkov

Architectural Complexity Measures of Recurrent Neural Networks

Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic

Object based Scene Representations using Fisher Scores of Local Subspace Projections

Mandar D Dixit, Nuno Vasconcelos

FPNN: Field Probing Neural Networks for 3D Data

Yangyan Li, Soeren Pirk, Hao Su, Charles R Qi, Leonidas Guibas

Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction

Hsiang-Fu Yu, Nikhil Rao, Inderjit S Dhillon

Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling

Chengtao Li, Suvrit Sra, Stefanie Jegelka

PAC-Bayesian Theory Meets Bayesian Inference

Pascal Germain, Francis Bach, Alexandre Lacoste, Simon Lacoste-Julien

Data Poisoning Attacks on Factorization-Based Collaborative Filtering

Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik

Reshaped Wirtinger Flow for Solving Quadratic System of Equations

Huishuai Zhang, Yingbin Liang

Learning feed-forward one-shot learners

Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip Torr, Andrea Vedaldi

Crowdsourced Clustering: Querying Edges vs Triangles

Ramya Korlakai Vinayak, Babak Hassibi

Unsupervised Learning of Spoken Language with Visual Context

David Harwath, Antonio Torralba, James Glass

Mixed Linear Regression with Multiple Components

Kai Zhong, Prateek Jain, Inderjit S Dhillon

Linear Feature Encoding for Reinforcement Learning

Zhao Song, Ronald E Parr, Xuejun Liao, Lawrence Carin

Causal meets Submodular: Subset Selection with Directed Information

Yuxun Zhou, Costas J Spanos

Maximization of Approximately Submodular Functions

Thibaut Horel, Yaron Singer

Convergence guarantees for kernel-based quadrature rules in misspecified settings

Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

Poisson-Gamma dynamical systems

Aaron Schein, Hanna Wallach, Mingyuan Zhou

One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities

Michalis Titsias RC AUEB

Tree-Structured Reinforcement Learning for Sequential Object Localization

Zequn Jie, Xiaodan Liang, Jiashi Feng, Xiaojie Jin, Wen Lu

Robust k-means: a Theoretical Revisit

ALEXANDROS GEORGOGIANNIS

Structured Matrix Recovery via the Generalized Dantzig Selector

Sheng Chen, Arindam Banerjee

Adaptive optimal training of animal behavior

Ji Hyun Bak, Jung Yoon Choi, Athena Akrami, Ilana Witten, Jonathan W Pillow

Deep Submodular Functions: Definitions and Learning

Brian W Dolhansky, Jeff A. Bilmes

Matrix Completion has No Spurious Local Minimum

Rong Ge, Jason Lee, Tengyu Ma

Learning Bound for Parameter Transfer Learning

Wataru Kumagai

Variational Information Maximization for Feature Selection

Shuyang Gao, Greg Ver Steeg, Aram Galstyan

Multivariate tests of association based on univariate tests

Ruth Heller, Yair Heller

Online and Differentially-Private Tensor Decomposition

Yining Wang, Anima Anandkumar

Deep Learning for Predicting Human Strategic Behavior

Jason S Hartford, James R Wright, Kevin Leyton-brown

Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain

Ian En-Hsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep K Ravikumar

SoundNet: Learning Sound Representations from Unlabeled Video

Yusuf Aytar, Carl Vondrick, Antonio Torralba

Composing graphical models with neural networks for structured representations and fast inference

Matthew J Johnson, David K. Duvenaud, Alex Wiltschko, Ryan P. Adams, Sandeep R Datta

Robustness of classifiers: from adversarial to random noise

Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

Automated scalable segmentation of neurons from multispectral images

Uygar Sümbül, Douglas Roossien, Dawen Cai, Fei Chen, Nicholas Barry

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever

Selective inference for group-sparse linear models

Fan Yang, Rina Foygel Barber, Prateek Jain, John Lafferty

Discriminative Gaifman Models

Mathias Niepert

Consistent Estimation of Functions of Data Missing Non-Monotonically and Not at Random

Ilya Shpitser

Clustering Signed Networks with the Geometric Mean of Laplacians

Pedro Mercado, Francesco Tudisco, Matthias Hein

Improved Dropout for Shallow and Deep Learning

Zhe Li, Boqing Gong, Tianbao Yang

Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages

Yin Cheng Ng, Pawel M Chilinski, Ricardo Silva

Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning

Jean-Bastien Grill, Michal Valko, Rémi Munos

A Minimax Approach to Supervised Learning

Farzan Farnia, David Tse