NeurIPS 2015

403 papers

Information-theoretic lower bounds for convex optimization with erroneous oracles

Yaron Singer, Jan Vondrak

The Self-Normalized Estimator for Counterfactual Learning

Adith Swaminathan, Thorsten Joachims

Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models

Juho Lee, Seungjin Choi

Streaming, Distributed Variational Inference for Bayesian Nonparametrics

Trevor Campbell, Julian Straub, John W. Fisher III, Jonathan P How

Online Learning for Adversaries with Memory: Price of Past Mistakes

Oren Anava, Elad Hazan, Shie Mannor

Enforcing balance allows local supervised learning in spiking recurrent networks

Ralph Bourdoukan, Sophie Deneve

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces

Takashi Takenouchi, Takafumi Kanamori

Semi-supervised Learning with Ladder Networks

Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko

Model-Based Relative Entropy Stochastic Search

Abbas Abdolmaleki, Rudolf Lioutikov, Nuno Lau, Luis Pualo Reis, Gerhard Neumann

Extending Gossip Algorithms to Distributed Estimation of U-statistics

Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon

Automatic Variational Inference in Stan

Alp Kucukelbir, Rajesh Ranganath, Andrew Gelman, David Blei

Super-Resolution Off the Grid

Qingqing Huang, Sham M. Kakade

Sparse Local Embeddings for Extreme Multi-label Classification

Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain

Planar Ultrametrics for Image Segmentation

Julian E Yarkony, Charless Fowlkes

Precision-Recall-Gain Curves: PR Analysis Done Right

Peter Flach, Meelis Kull

Spatial Transformer Networks

Max Jaderberg, Karen Simonyan, Andrew Zisserman, Koray Kavukcuoglu

On-the-Job Learning with Bayesian Decision Theory

Keenon Werling, Arun Tejasvi Chaganty, Percy Liang, Christopher D. Manning

A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements

Qinqing Zheng, John Lafferty

Kullback-Leibler Proximal Variational Inference

Mohammad Emtiyaz Khan, Pierre Baque, Francois Fleuret, Pascal Fua

Halting in Random Walk Kernels

Mahito Sugiyama, Karsten Borgwardt

Regressive Virtual Metric Learning

Michaël Perrot, Amaury Habrard

Latent Bayesian melding for integrating individual and population models

Mingjun Zhong, Nigel Goddard, Charles Sutton

Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits

Huasen Wu, R. Srikant, Xin Liu, Chong Jiang

Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning

Christoph Dann, Emma Brunskill

A Bayesian Framework for Modeling Confidence in Perceptual Decision Making

Koosha Khalvati, Rajesh P. Rao

Inference for determinantal point processes without spectral knowledge

Rémi Bardenet, Michalis Titsias RC AUEB

Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models

Michael C Hughes, William T Stephenson, Erik Sudderth

Natural Neural Networks

Guillaume Desjardins, Karen Simonyan, Razvan Pascanu, Koray Kavukcuoglu

LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements

CHRISTOS THRAMPOULIDIS, Ehsan Abbasi, Babak Hassibi

Lifted Inference Rules With Constraints

Happy Mittal, Anuj Mahajan, Vibhav G Gogate, Parag Singla

Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents

Mithun Chakraborty, Sanmay Das

Sparse PCA via Bipartite Matchings

Megasthenis Asteris, Dimitris Papailiopoulos, Anastasios Kyrillidis, Alexandros G Dimakis

Generative Image Modeling Using Spatial LSTMs

Lucas Theis, Matthias Bethge

Differentially Private Learning of Structured Discrete Distributions

Ilias Diakonikolas, Moritz Hardt, Ludwig Schmidt

Learning Bayesian Networks with Thousands of Variables

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

Fast and Accurate Inference of Plackett–Luce Models

Lucas Maystre, Matthias Grossglauser

Pointer Networks

Oriol Vinyals, Meire Fortunato, Navdeep Jaitly

Unlocking neural population non-stationarities using hierarchical dynamics models

Mijung Park, Gergo Bohner, Jakob H. Macke

Local Smoothness in Variance Reduced Optimization

Daniel Vainsencher, Han Liu, Tong Zhang

A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure

Peter Schulam, Suchi Saria

GP Kernels for Cross-Spectrum Analysis

Kyle R Ulrich, David E Carlson, Kafui Dzirasa, Lawrence Carin

Practical and Optimal LSH for Angular Distance

Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya Razenshteyn, Ludwig Schmidt

Grammar as a Foreign Language

Oriol Vinyals, Łukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever

Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

Armand Joulin, Tomas Mikolov

Interactive Control of Diverse Complex Characters with Neural Networks

Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, Emanuel V. Todorov

Character-level Convolutional Networks for Text Classification

Xiang Zhang, Junbo Zhao, Yann LeCun

Fast and Memory Optimal Low-Rank Matrix Approximation

Se-Young Yun, marc lelarge, Alexandre Proutiere

Training Very Deep Networks

Rupesh K Srivastava, Klaus Greff, Jürgen Schmidhuber

Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process

Ye Wang, David B. Dunson, David B Dunson

Combinatorial Cascading Bandits

Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári

Optimal Testing for Properties of Distributions

Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

Cameron Musco, Christopher Musco

Spectral Norm Regularization of Orthonormal Representations for Graph Transduction

Rakesh Shivanna, Bibaswan K Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis Bach

b-bit Marginal Regression

Martin Slawski, Ping Li

Robust Regression via Hard Thresholding

Kush Bhatia, Prateek Jain, Purushottam Kar

Adaptive Online Learning

Dylan J Foster, Alexander Rakhlin, Karthik Sridharan

Fast Classification Rates for High-dimensional Gaussian Generative Models

Tianyang Li, Adarsh Prasad, Pradeep K Ravikumar

Learning spatiotemporal trajectories from manifold-valued longitudinal data

Jean-Baptiste SCHIRATTI, Stéphanie ALLASSONNIERE, Olivier Colliot, Stanley DURRLEMAN

Expressing an Image Stream with a Sequence of Natural Sentences

Cesc C Park, Gunhee Kim

Closed-form Estimators for High-dimensional Generalized Linear Models

Eunho Yang, Aurelie C. Lozano, Pradeep K Ravikumar

A class of network models recoverable by spectral clustering

Yali Wan, Marina Meila

Sampling from Probabilistic Submodular Models

Alkis Gotovos, Hamed Hassani, Andreas Krause

Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets

Justin Domke

Learning with Incremental Iterative Regularization

Lorenzo Rosasco, Silvia Villa

Efficient Non-greedy Optimization of Decision Trees

Mohammad Norouzi, Maxwell Collins, Matthew A Johnson, David J Fleet, Pushmeet Kohli

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

Learning Continuous Control Policies by Stochastic Value Gradients

Nicolas Heess, Gregory Wayne, David Silver, Timothy Lillicrap, Tom Erez

High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality

Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu

Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy

Marylou Gabrie, Eric W Tramel, Florent Krzakala

Local Expectation Gradients for Black Box Variational Inference

Michalis Titsias RC AUEB, Miguel Lázaro-Gredilla

Time-Sensitive Recommendation From Recurrent User Activities

Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song

Efficient and Robust Automated Machine Learning

Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum

Backpropagation for Energy-Efficient Neuromorphic Computing

Steve K Esser, Rathinakumar Appuswamy, Paul Merolla, John V. Arthur, Dharmendra S Modha

Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis

Jimei Yang, Scott E Reed, Ming-Hsuan Yang, Honglak Lee

Attention-Based Models for Speech Recognition

Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio

Statistical Model Criticism using Kernel Two Sample Tests

James R Lloyd, Zoubin Ghahramani

Bayesian Optimization with Exponential Convergence

Kenji Kawaguchi, Leslie Pack Kaelbling, Tomás Lozano-Pérez

Policy Evaluation Using the Ω-Return

Philip S. Thomas, Scott Niekum, Georgios Theocharous, George Konidaris

Efficient and Parsimonious Agnostic Active Learning

Tzu-kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire

Combinatorial Bandits Revisited

Richard Combes, Mohammad Sadegh Talebi Mazraeh Shahi, Alexandre Proutiere, marc lelarge

Barrier Frank-Wolfe for Marginal Inference

Rahul G Krishnan, Simon Lacoste-Julien, David Sontag

A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding

Yuval Harel, Ron Meir, Manfred Opper

Optimal Ridge Detection using Coverage Risk

Yen-Chi Chen, Christopher R Genovese, Shirley Ho, Larry Wasserman

Online Gradient Boosting

Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo

Data Generation as Sequential Decision Making

Philip Bachman, Doina Precup

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent

Ian En-Hsu Yen, Kai Zhong, Cho-jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation

Scott Linderman, Matthew J Johnson, Ryan P. Adams

Infinite Factorial Dynamical Model

Isabel Valera, Francisco Ruiz, Lennart Svensson, Fernando Pérez-Cruz

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

Xingjian SHI, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong

Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data

Danilo Bzdok, Michael Eickenberg, Olivier Grisel, Bertrand Thirion, Gael Varoquaux

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry Wasserman, james m robins

Matrix Completion with Noisy Side Information

Kai-Yang Chiang, Cho-jui Hsieh, Inderjit S Dhillon

Differentially private subspace clustering

Yining Wang, Yu-Xiang Wang, Aarti Singh

Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models

Akihiro Kishimoto, Radu Marinescu, Adi Botea

Less is More: Nyström Computational Regularization

Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco

Top-k Multiclass SVM

Maksim Lapin, Matthias Hein, Bernt Schiele

Robust Portfolio Optimization

Huitong Qiu, Fang Han, Han Liu, Brian Caffo

SubmodBoxes: Near-Optimal Search for a Set of Diverse Object Proposals

Qing Sun, Dhruv Batra

Stochastic Online Greedy Learning with Semi-bandit Feedbacks

Tian Lin, Jian Li, Wei Chen

A fast, universal algorithm to learn parametric nonlinear embeddings

Miguel Á. Carreira-Perpiñán, Max Vladymyrov