NeurIPS 2016

569 papers

A Probabilistic Model of Social Decision Making based on Reward Maximization

Koosha Khalvati, Seongmin A. Park, Jean-Claude Dreher, Rajesh P. Rao

Stochastic Variance Reduction Methods for Saddle-Point Problems

Balamurugan Palaniappan, Francis Bach

Edge-exchangeable graphs and sparsity

Diana Cai, Trevor Campbell, Tamara Broderick

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

Jian Wu, Peter Frazier

Algorithms and matching lower bounds for approximately-convex optimization

Andrej Risteski, Yuanzhi Li

Quantized Random Projections and Non-Linear Estimation of Cosine Similarity

Ping Li, Michael Mitzenmacher, Martin Slawski

Density Estimation via Discrepancy Based Adaptive Sequential Partition

Dangna Li, Kun Yang, Wing Hung Wong

Hardness of Online Sleeping Combinatorial Optimization Problems

Satyen Kale, Chansoo Lee, Dávid Pál

Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers

Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan J Tibshirani

Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis

Yoshinobu Kawahara

Adaptive Averaging in Accelerated Descent Dynamics

Walid Krichene, Alexandre Bayen, Peter L. Bartlett, Peter L Bartlett

Deep ADMM-Net for Compressive Sensing MRI

yan yang, Jian Sun, Huibin Li, Zongben Xu

Professor Forcing: A New Algorithm for Training Recurrent Networks

Alex M Lamb, Anirudh Goyal ALIAS PARTH GOYAL, Ying Zhang, Saizheng Zhang, Aaron C. Courville

Efficient Second Order Online Learning by Sketching

Haipeng Luo, Alekh Agarwal, Nicolò Cesa-bianchi, John Langford

Higher-Order Factorization Machines

Mathieu Blondel, Akinori Fujino, Naonori Ueda, Masakazu Ishihata

End-to-End Goal-Driven Web Navigation

Rodrigo Nogueira, Kyunghyun Cho

Learning under uncertainty: a comparison between R-W and Bayesian approach

He Huang, Martin Paulus

MetaGrad: Multiple Learning Rates in Online Learning

Tim van Erven, Wouter M. Koolen

Exponential expressivity in deep neural networks through transient chaos

Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-dickstein, Surya Ganguli

Learning Bayesian networks with ancestral constraints

Eunice Yuh-Jie Chen, Yujia Shen, Arthur Choi, Adnan Darwiche

Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs

Yu-Xiong Wang, Martial Hebert

Active Nearest-Neighbor Learning in Metric Spaces

Aryeh Kontorovich, Sivan Sabato, Ruth Urner

Improving PAC Exploration Using the Median Of Means

Jason Pazis, Ronald E Parr, Jonathan P How

Learning brain regions via large-scale online structured sparse dictionary learning

Elvis DOHMATOB, Arthur Mensch, Gael Varoquaux, Bertrand Thirion

Fast and accurate spike sorting of high-channel count probes with KiloSort

Marius Pachitariu, Nicholas A Steinmetz, Shabnam N Kadir, Matteo Carandini, Kenneth D Harris

Supervised Word Mover's Distance

Gao Huang, Chuan Guo, Matt J Kusner, Yu Sun, Fei Sha

A Communication-Efficient Parallel Algorithm for Decision Tree

Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye

Efficient state-space modularization for planning: theory, behavioral and neural signatures

Daniel McNamee, Daniel M. Wolpert, Máté Lengyel

Optimal Architectures in a Solvable Model of Deep Networks

Jonathan Kadmon, Haim Sompolinsky

Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models

Tomoharu Iwata, Makoto Yamada

On Valid Optimal Assignment Kernels and Applications to Graph Classification

Nils M. Kriege, Pierre-Louis Giscard, Richard Wilson

Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

Xiaojiao Mao, Chunhua Shen, Yu-Bin Yang

Measuring the reliability of MCMC inference with bidirectional Monte Carlo

Roger B Grosse, Siddharth Ancha, Daniel M. Roy

Optimal Sparse Linear Encoders and Sparse PCA

Malik Magdon-Ismail, Christos Boutsidis

Single Pass PCA of Matrix Products

Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G Dimakis

Single-Image Depth Perception in the Wild

Weifeng Chen, Zhao Fu, Dawei Yang, Jia Deng

Maximal Sparsity with Deep Networks?

Bo Xin, Yizhou Wang, Wen Gao, David Wipf, Baoyuan Wang

Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models

Juho Lee, Lancelot F James, Seungjin Choi

Variational Bayes on Monte Carlo Steroids

Aditya Grover, Stefano Ermon

Threshold Bandits, With and Without Censored Feedback

Jacob D. Abernethy, Kareem Amin, Ruihao Zhu

Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction

Jacob Steinhardt, Gregory Valiant, Moses Charikar

A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing

Ming Lin, Jieping Ye

Finding significant combinations of features in the presence of categorical covariates

Laetitia Papaxanthos, Felipe Llinares-López, Dean Bodenham, Karsten Borgwardt

Interpretable Distribution Features with Maximum Testing Power

Wittawat Jitkrittum, Zoltan Szabo, Kacper P Chwialkowski, Arthur Gretton

Bi-Objective Online Matching and Submodular Allocations

Hossein Esfandiari, Nitish Korula, Vahab Mirrokni

A Sparse Interactive Model for Matrix Completion with Side Information

Jin Lu, Guannan Liang, Jiangwen Sun, Jinbo Bi

An equivalence between high dimensional Bayes optimal inference and M-estimation

Madhu Advani, Surya Ganguli

Budgeted stream-based active learning via adaptive submodular maximization

Kaito Fujii, Hisashi Kashima

Convolutional Neural Fabrics

Shreyas Saxena, Jakob Verbeek

Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks

Noah Apthorpe, Alexander Riordan, Robert Aguilar, Jan Homann, Yi Gu

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

Yarin Gal, Zoubin Ghahramani

Dialog-based Language Learning

Jason E Weston

Integrated perception with recurrent multi-task neural networks

Hakan Bilen, Andrea Vedaldi

A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics

William Hoiles, Mihaela van der Schaar

Exponential Family Embeddings

Maja Rudolph, Francisco Ruiz, Stephan Mandt, David Blei

Fast Distributed Submodular Cover: Public-Private Data Summarization

Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst

Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods

Andrej Risteski, Yuanzhi Li

Generating Videos with Scene Dynamics

Carl Vondrick, Hamed Pirsiavash, Antonio Torralba

Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo

Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël RICHARD

Achieving budget-optimality with adaptive schemes in crowdsourcing

Ashish Khetan, Sewoong Oh

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

Tianfan Xue, Jiajun Wu, Katherine Bouman, Bill Freeman

Bayesian Intermittent Demand Forecasting for Large Inventories

Matthias W Seeger, David Salinas, Valentin Flunkert

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks

Hao Wang, Xingjian SHI, Dit-Yan Yeung

Conditional Generative Moment-Matching Networks

Yong Ren, Jun Zhu, Jialian Li, Yucen Luo

Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics

Wei-Shou Hsu, Pascal Poupart

Tagger: Deep Unsupervised Perceptual Grouping

Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hao, Harri Valpola

A Locally Adaptive Normal Distribution

Georgios Arvanitidis, Lars K. Hansen, Søren Hauberg

Eliciting Categorical Data for Optimal Aggregation

Chien-Ju Ho, Rafael Frongillo, Yiling Chen