NeurIPS 2013

360 papers

Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC

Roger Frigola, Fredrik Lindsten, Thomas B Schön, Carl Edward Rasmussen

Optimistic policy iteration and natural actor-critic: A unifying view and a non-optimality result

Paul Wagner

Zero-Shot Learning Through Cross-Modal Transfer

Richard Socher, Milind Ganjoo, Christopher D. Manning, Andrew Ng

Demixing odors - fast inference in olfaction

Agnieszka Grabska-Barwinska, Jeff Beck, Alexandre Pouget, Peter Latham

Estimating LASSO Risk and Noise Level

Mohsen Bayati, Murat A Erdogdu, Andrea Montanari

Regression-tree Tuning in a Streaming Setting

Samory Kpotufe, Francesco Orabona

An Approximate, Efficient LP Solver for LP Rounding

Srikrishna Sridhar, Stephen Wright, Christopher Re, Ji Liu, Victor Bittorf

Online Learning with Costly Features and Labels

Navid Zolghadr, Gabor Bartok, Russell Greiner, András György, Csaba Szepesvári

Adaptivity to Local Smoothness and Dimension in Kernel Regression

Samory Kpotufe, Vikas Garg

Conditional Random Fields via Univariate Exponential Families

Eunho Yang, Pradeep K Ravikumar, Genevera I Allen, Zhandong Liu

A multi-agent control framework for co-adaptation in brain-computer interfaces

Josh S Merel, Roy Fox, Tony Jebara, Liam Paninski

Scalable Inference for Logistic-Normal Topic Models

Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang

Predictive PAC Learning and Process Decompositions

Cosma Shalizi, Aryeh Kontorovich

Estimation, Optimization, and Parallelism when Data is Sparse

John Duchi, Brendan Mcmahan, Michael I. Jordan, Michael I Jordan

Learning Multi-level Sparse Representations

Ferran Diego Andilla, Fred A. Hamprecht

Unsupervised Structure Learning of Stochastic And-Or Grammars

Kewei Tu, Maria Pavlovskaia, Song-chun Zhu

Phase Retrieval using Alternating Minimization

Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi

Tracking Time-varying Graphical Structure

Erich Kummerfeld, David Danks

Perfect Associative Learning with Spike-Timing-Dependent Plasticity

Christian Albers, Maren Westkott, Klaus Pawelzik

Reshaping Visual Datasets for Domain Adaptation

Boqing Gong, Kristen Grauman, Fei Sha

Matrix factorization with binary components

Martin Slawski, Matthias Hein, Pavlo Lutsik

Fast Determinantal Point Process Sampling with Application to Clustering

Byungkon Kang

Low-Rank Matrix and Tensor Completion via Adaptive Sampling

Akshay Krishnamurthy, Aarti Singh

Training and Analysing Deep Recurrent Neural Networks

Michiel Hermans, Benjamin Schrauwen

Extracting regions of interest from biological images with convolutional sparse block coding

Marius Pachitariu, Adam M Packer, Noah Pettit, Henry Dalgleish, Michael Hausser

Learning Gaussian Graphical Models with Observed or Latent FVSs

Ying Liu, Alan Willsky

Synthesizing Robust Plans under Incomplete Domain Models

Tuan A Nguyen, Subbarao Kambhampati, Minh Do

Translating Embeddings for Modeling Multi-relational Data

Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko

Optimal integration of visual speed across different spatiotemporal frequency channels

Matjaz Jogan, Alan Stocker

Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching

Marcelo Fiori, Pablo Sprechmann, Joshua Vogelstein, Pablo Musé, Guillermo Sapiro

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables

Cho-jui Hsieh, Inderjit S Dhillon, Pradeep K Ravikumar, Russell Poldrack, Mátyás A. Sustik

Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors

Xiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma

Multiclass Total Variation Clustering

Xavier Bresson, Thomas Laurent, David Uminsky, James von Brecht

A Gang of Bandits

Nicolò Cesa-bianchi, Claudio Gentile, Giovanni Zappella

Integrated Non-Factorized Variational Inference

Shaobo Han, Xuejun Liao, Lawrence Carin

Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization

Nataliya Shapovalova, Michalis Raptis, Leonid Sigal, Greg Mori

Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits

Ben Shababo, Brooks Paige, Ari Pakman, Liam Paninski

Learning to Pass Expectation Propagation Messages

Nicolas Heess, Daniel Tarlow, John Winn

Convergence of Monte Carlo Tree Search in Simultaneous Move Games

Viliam Lisy, Vojta Kovarik, Marc Lanctot, Branislav Bosansky

Efficient Online Inference for Bayesian Nonparametric Relational Models

Dae Il Kim, Prem Gopalan, David Blei, Erik Sudderth

Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression

Michalis Titsias RC AUEB, Miguel Lázaro-Gredilla

Convex Tensor Decomposition via Structured Schatten Norm Regularization

Ryota Tomioka, Taiji Suzuki

Graphical Models for Inference with Missing Data

Karthika Mohan, Judea Pearl, Jin Tian

A Novel Two-Step Method for Cross Language Representation Learning

Min Xiao, Yuhong Guo

Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel

Tai Qin, Karl Rohe

Reinforcement Learning in Robust Markov Decision Processes

Shiau Hong Lim, Huan Xu, Shie Mannor

Learning and using language via recursive pragmatic reasoning about other agents

Nathaniel J Smith, Noah Goodman, Michael Frank

Multi-Prediction Deep Boltzmann Machines

Ian Goodfellow, Mehdi Mirza, Aaron Courville, Yoshua Bengio

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks

Junming Yin, Qirong Ho, Eric P. Xing, Eric P Xing

Accelerated Mini-Batch Stochastic Dual Coordinate Ascent

Shai Shalev-shwartz, Tong Zhang

A Kernel Test for Three-Variable Interactions

Dino Sejdinovic, Arthur Gretton, Wicher Bergsma

A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles

Jinwoo Shin, Andrew E Gelfand, Misha Chertkov

Sequential Transfer in Multi-armed Bandit with Finite Set of Models

Mohammad Gheshlaghi azar, Alessandro Lazaric, Emma Brunskill

On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation

Harikrishna Narasimhan, Shivani Agarwal

Robust Bloom Filters for Large MultiLabel Classification Tasks

Moustapha M Cisse, Nicolas Usunier, Thierry Artières, Patrick Gallinari

On model selection consistency of penalized M-estimators: a geometric theory

Jason Lee, Yuekai Sun, Jonathan E Taylor

Transportability from Multiple Environments with Limited Experiments

Elias Bareinboim, Sanghack Lee, Vasant Honavar, Judea Pearl

Third-Order Edge Statistics: Contour Continuation, Curvature, and Cortical Connections

Matthew Lawlor, Steven W Zucker

Approximate Gaussian process inference for the drift function in stochastic differential equations

Andreas Ruttor, Philipp Batz, Manfred Opper

Inferring neural population dynamics from multiple partial recordings of the same neural circuit

Srini Turaga, Lars Buesing, Adam M Packer, Henry Dalgleish, Noah Pettit