NeurIPS 2016

569 papers

Minimizing Quadratic Functions in Constant Time

Kohei Hayashi, Yuichi Yoshida

Natural-Parameter Networks: A Class of Probabilistic Neural Networks

Hao Wang, Xingjian SHI, Dit-Yan Yeung

Generating Long-term Trajectories Using Deep Hierarchical Networks

Stephan Zheng, Yisong Yue, Jennifer Hobbs

Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition

Ahmed M. Alaa, Mihaela van der Schaar

General Tensor Spectral Co-clustering for Higher-Order Data

Tao Wu, Austin R Benson, David F Gleich

Optimal Learning for Multi-pass Stochastic Gradient Methods

Junhong Lin, Lorenzo Rosasco

Visual Question Answering with Question Representation Update (QRU)

Ruiyu Li, Jiaya Jia

Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions

Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal

End-to-End Kernel Learning with Supervised Convolutional Kernel Networks

Julien Mairal

Human Decision-Making under Limited Time

Pedro A Ortega, Alan Stocker

Fast Active Set Methods for Online Spike Inference from Calcium Imaging

Johannes Friedrich, Liam Paninski

Can Active Memory Replace Attention?

Łukasz Kaiser, Samy Bengio

Mixed vine copulas as joint models of spike counts and local field potentials

Arno Onken, Stefano Panzeri

Learning to learn by gradient descent by gradient descent

Marcin Andrychowicz, Misha Denil, Sergio Gómez, Matthew W Hoffman, David Pfau

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity

Eugene Belilovsky, Gael Varoquaux, Matthew B. Blaschko, Matthew B Blaschko

Neural Universal Discrete Denoiser

Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon

Semiparametric Differential Graph Models

Pan Xu, Quanquan Gu

The Generalized Reparameterization Gradient

Francisco R Ruiz, Michalis Titsias RC AUEB, David Blei

On Multiplicative Integration with Recurrent Neural Networks

Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov

SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling

Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros

Proximal Deep Structured Models

Shenlong Wang, Sanja Fidler, Raquel Urtasun

Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?

Arturo Deza, Miguel Eckstein

Agnostic Estimation for Misspecified Phase Retrieval Models

Matey Neykov, Zhaoran Wang, Han Liu

Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum

Ancestral Causal Inference

Sara Magliacane, Tom Claassen, Joris M. Mooij

Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

Ayan Chakrabarti, Jingyu Shao, Greg Shakhnarovich

Lifelong Learning with Weighted Majority Votes

Anastasia Pentina, Ruth Urner

Learning and Forecasting Opinion Dynamics in Social Networks

Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez Rodriguez

High resolution neural connectivity from incomplete tracing data using nonnegative spline regression

Kameron D Harris, Stefan Mihalas, Eric Shea-Brown

Linear Contextual Bandits with Knapsacks

Shipra Agrawal, Nikhil Devanur

Deep Learning without Poor Local Minima

Kenji Kawaguchi

Unsupervised Risk Estimation Using Only Conditional Independence Structure

Jacob Steinhardt, Percy Liang

The Forget-me-not Process

Kieran Milan, Joel Veness, James Kirkpatrick, Michael Bowling, Anna Koop

A Pseudo-Bayesian Algorithm for Robust PCA

Tae-Hyun Oh, Yasuyuki Matsushita, In Kweon, David Wipf

DeepMath - Deep Sequence Models for Premise Selection

Geoffrey Irving, Christian Szegedy, Alexander A Alemi, Niklas Een, Francois Chollet

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions

Mikhail Figurnov, Aizhan Ibraimova, Dmitry P Vetrov, Pushmeet Kohli

Graphical Time Warping for Joint Alignment of Multiple Curves

Yizhi Wang, David J. Miller, Kira Poskanzer, Yue Wang, Lin Tian

Adaptive Neural Compilation

Rudy R Bunel, Alban Desmaison, Pawan K Mudigonda, Pushmeet Kohli, Philip Torr

On Explore-Then-Commit strategies

Aurélien Garivier, Tor Lattimore, Emilie Kaufmann

Namrata Vaswani, Han Guo

Gaussian Processes for Survival Analysis

Tamara Fernandez, Nicolas Rivera, Yee Whye Teh

Disentangling factors of variation in deep representation using adversarial training

Michael F Mathieu, Junbo Jake Zhao, Junbo Zhao, Aditya Ramesh, Pablo Sprechmann

Learning Additive Exponential Family Graphical Models via ℓ_2,1-norm Regularized M-Estimation

Xiaotong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

Tim Salimans, Diederik P. Kingma

Variational Autoencoder for Deep Learning of Images, Labels and Captions

Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li

Fairness in Learning: Classic and Contextual Bandits

Matthew Joseph, Michael Kearns, Jamie H Morgenstern, Aaron Roth

Dense Associative Memory for Pattern Recognition

Dmitry Krotov, John J. Hopfield

Optimal Binary Classifier Aggregation for General Losses

Akshay Balsubramani, Yoav S Freund

A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization

Jingwei Liang, Jalal Fadili, Gabriel Peyré

Parameter Learning for Log-supermodular Distributions

Tatiana Shpakova, Francis Bach

Exact Recovery of Hard Thresholding Pursuit

Xiaotong Yuan, Ping Li, Tong Zhang

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee

Combinatorial semi-bandit with known covariance

Rémy Degenne, Vianney Perchet

Learning Kernels with Random Features

Aman Sinha, John C. Duchi

Efficient Neural Codes under Metabolic Constraints

Zhuo Wang, Xue-xin Wei, Alan Stocker, Daniel D. Lee, Daniel D Lee

Deep Neural Networks with Inexact Matching for Person Re-Identification

Arulkumar Subramaniam, Moitreya Chatterjee, Anurag Mittal

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much

Bryan D He, Christopher M De Sa, Ioannis Mitliagkas, Christopher Re

Unsupervised Learning from Noisy Networks with Applications to Hi-C Data

Bo Wang, Junjie Zhu, Armin Pourshafeie, Oana Ursu, Serafim Batzoglou

Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables

Mauro Scanagatta, Giorgio Corani, Cassio P de Campos, Marco Zaffalon

Contextual semibandits via supervised learning oracles

Akshay Krishnamurthy, Alekh Agarwal, Miro Dudik

Scaled Least Squares Estimator for GLMs in Large-Scale Problems

Murat A Erdogdu, Lee H Dicker, Mohsen Bayati

Kernel Bayesian Inference with Posterior Regularization

Yang Song, Jun Zhu, Yong Ren

Joint quantile regression in vector-valued RKHSs

Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits

Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire

Faster Projection-free Convex Optimization over the Spectrahedron

Dan Garber

Learning Infinite RBMs with Frank-Wolfe

Wei Ping, Qiang Liu, Alex Ihler

Select-and-Sample for Spike-and-Slab Sparse Coding

Abdul-saboor Sheikh, Jörg Lücke

Improved Variational Inference with Inverse Autoregressive Flow

Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever

Active Learning from Imperfect Labelers

Songbai Yan, Kamalika Chaudhuri, Tara Javidi

The Robustness of Estimator Composition

Pingfan Tang, Jeff M Phillips

Data driven estimation of Laplace-Beltrami operator

Frederic Chazal, Ilaria Giulini, Bertrand Michel

Constraints Based Convex Belief Propagation

Yaniv Tenzer, Alex Schwing, Kevin Gimpel, Tamir Hazan

Launch and Iterate: Reducing Prediction Churn

Mahdi Milani Fard, Quentin Cormier, Kevin Canini, Maya Gupta

Satisfying Real-world Goals with Dataset Constraints

Gabriel Goh, Andrew Cotter, Maya Gupta, Michael P Friedlander

Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling

Maria-Florina F Balcan, Hongyang Zhang

A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order

Xiangru Lian, Huan Zhang, Cho-jui Hsieh, Yijun Huang, Ji Liu

Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning

Wouter M. Koolen, Peter Grünwald, Tim van Erven

Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes

Dan Garber, Ofer Meshi

Full-Capacity Unitary Recurrent Neural Networks

Scott Wisdom, Thomas Powers, John Hershey, Jonathan Le Roux, Les Atlas

Unsupervised Learning for Physical Interaction through Video Prediction

Chelsea Finn, Ian Goodfellow, Sergey Levine

Operator Variational Inference

Rajesh Ranganath, Dustin Tran, Jaan Altosaar, David Blei

Learning a Metric Embedding for Face Recognition using the Multibatch Method

Oren Tadmor, Tal Rosenwein, Shai Shalev-shwartz, Yonatan Wexler, Amnon Shashua

Binarized Neural Networks

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio

Linear Relaxations for Finding Diverse Elements in Metric Spaces

Aditya Bhaskara, Mehrdad Ghadiri, Vahab Mirrokni, Ola Svensson

A Bandit Framework for Strategic Regression

Yang Liu, Yiling Chen

High Dimensional Structured Superposition Models

Qilong Gu, Arindam Banerjee

Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm

Kejun Huang, Xiao Fu, Nikolaos D. Sidiropoulos

Fast and Provably Good Seedings for k-Means

Olivier Bachem, Mario Lucic, Hamed Hassani, Andreas Krause

Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information

Alexander Shishkin, Anastasia Bezzubtseva, Alexey Drutsa, Ilia Shishkov, Ekaterina Gladkikh

Average-case hardness of RIP certification

Tengyao Wang, Quentin Berthet, Yaniv Plan

Direct Feedback Alignment Provides Learning in Deep Neural Networks

Arild Nøkland

Quantum Perceptron Models

Ashish Kapoor, Nathan Wiebe, Krysta Svore

Mistake Bounds for Binary Matrix Completion

Mark Herbster, Stephen Pasteris, Massimiliano Pontil

Leveraging Sparsity for Efficient Submodular Data Summarization

Erik Lindgren, Shanshan Wu, Alexandros G Dimakis

Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA

Aapo Hyvärinen, Hiroshi Morioka

An urn model for majority voting in classification ensembles

Victor Soto, Alberto Suárez, Gonzalo Martinez-Muñoz

Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition

Shizhong Han, Zibo Meng, AHMED-SHEHAB KHAN, Yan Tong

Xiangyu Wang, Chenlei Leng, David B. Dunson, David B Dunson

Nearly Isometric Embedding by Relaxation

James McQueen, Marina Meila, Dominique Joncas

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

Sebastian Nowozin, Botond Cseke, Ryota Tomioka