NeurIPS 2012

370 papers

Fully Bayesian inference for neural models with negative-binomial spiking

James Scott, Jonathan W Pillow, Jonathan W. Pillow

Probabilistic Low-Rank Subspace Clustering

S. D. Babacan, Shinichi Nakajima, Minh Do

Active Learning of Multi-Index Function Models

Tyagi Hemant, Volkan Cevher

A Neural Autoregressive Topic Model

Hugo Larochelle, Stanislas Lauly

Newton-Like Methods for Sparse Inverse Covariance Estimation

Figen Oztoprak, Jorge Nocedal, Steven Rennie, Peder A. Olsen

Learning Manifolds with K-Means and K-Flats

Guillermo Canas, Tomaso Poggio, Lorenzo Rosasco

Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation

Tuo Zhao, Kathryn Roeder, Han Liu

Collaborative Gaussian Processes for Preference Learning

Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, José M. Hernández-lobato

Transelliptical Graphical Models

Han Liu, Fang Han, Cun-hui Zhang

A nonparametric variable clustering model

Konstantina Palla, Zoubin Ghahramani, David A. Knowles

Multimodal Learning with Deep Boltzmann Machines

Nitish Srivastava, Ruslan Salakhutdinov

A Polynomial-time Form of Robust Regression

Özlem Aslan, Dale Schuurmans, Yaoliang Yu, Yao-Liang Yu

Hierarchical spike coding of sound

Yan Karklin, Chaitanya Ekanadham, Eero P. Simoncelli

Identification of Recurrent Patterns in the Activation of Brain Networks

Firdaus Janoos, Weichang Li, Niranjan Subrahmanya, Istvan Morocz, William Wells

Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning

Matthew Der, Lawrence K. Saul

Value Pursuit Iteration

Amir M. Farahmand, Doina Precup

A Conditional Multinomial Mixture Model for Superset Label Learning

Liping Liu, Thomas G. Dietterich

Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems

Morteza Ibrahimi, Adel Javanmard, Benjamin V. Roy

A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function

Pedro Ortega, Jordi Grau-moya, Tim Genewein, David Balduzzi, Daniel Braun

Unsupervised Template Learning for Fine-Grained Object Recognition

Shulin Yang, Liefeng Bo, Jue Wang, Linda G. Shapiro

Dip-means: an incremental clustering method for estimating the number of clusters

Argyris Kalogeratos, Aristidis Likas

Local Supervised Learning through Space Partitioning

Joseph Wang, Venkatesh Saligrama

Multi-task Vector Field Learning

Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He

Semiparametric Principal Component Analysis

Fang Han, Han Liu

Action-Model Based Multi-agent Plan Recognition

Hankz H. Zhuo, Qiang Yang, Subbarao Kambhampati

Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs

Michael Collins, Shay B. Cohen

Random Utility Theory for Social Choice

Hossein Azari, David Parks, Lirong Xia

Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach

Dijun Luo, Heng Huang, Feiping Nie, Chris H. Ding

Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model

Sander M. Bohte

Bayesian models for Large-scale Hierarchical Classification

Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-mizil

From Deformations to Parts: Motion-based Segmentation of 3D Objects

Soumya Ghosh, Matthew Loper, Erik B. Sudderth, Michael J. Black

Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress

Manuel Lopes, Tobias Lang, Marc Toussaint, Pierre-yves Oudeyer

Bayesian Probabilistic Co-Subspace Addition

Lei Shi

Algorithms for Learning Markov Field Policies

Abdeslam Boularias, Jan R. Peters, Oliver B. Kroemer

An Integer Optimization Approach to Associative Classification

Dimitris Bertsimas, Allison Chang, Cynthia Rudin

Minimizing Uncertainty in Pipelines

Nilesh Dalvi, Aditya Parameswaran, Vibhor Rastogi

Learning Multiple Tasks using Shared Hypotheses

Koby Crammer, Yishay Mansour

Learning from Distributions via Support Measure Machines

Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf

Training sparse natural image models with a fast Gibbs sampler of an extended state space

Lucas Theis, Jascha Sohl-dickstein, Matthias Bethge

Iterative ranking from pair-wise comparisons

Sahand Negahban, Sewoong Oh, Devavrat Shah

A Marginalized Particle Gaussian Process Regression

Yali Wang, Brahim Chaib-draa

Sparse Prediction with the k-Support Norm

Andreas Argyriou, Rina Foygel, Nathan Srebro

Cardinality Restricted Boltzmann Machines

Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov

Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination

Won H. Kim, Deepti Pachauri, Charles Hatt, Moo. K. Chung, Sterling Johnson

A new metric on the manifold of kernel matrices with application to matrix geometric means

Suvrit Sra

Minimizing Sparse High-Order Energies by Submodular Vertex-Cover

Andrew Delong, Olga Veksler, Anton Osokin, Yuri Boykov

Max-Margin Structured Output Regression for Spatio-Temporal Action Localization

Du Tran, Junsong Yuan

Reducing statistical time-series problems to binary classification

Daniil Ryabko, Jeremie Mary

Active Comparison of Prediction Models

Christoph Sawade, Niels Landwehr, Tobias Scheffer

Ensemble weighted kernel estimators for multivariate entropy estimation

Kumar Sricharan, Alfred O. Hero

A mechanistic model of early sensory processing based on subtracting sparse representations

Shaul Druckmann, Tao Hu, Dmitri B. Chklovskii

Analyzing 3D Objects in Cluttered Images

Mohsen Hejrati, Deva Ramanan

Monte Carlo Methods for Maximum Margin Supervised Topic Models

Qixia Jiang, Jun Zhu, Maosong Sun, Eric P. Xing

A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets

Nicolas L. Roux, Mark Schmidt, Francis R. Bach

Automatic Feature Induction for Stagewise Collaborative Filtering

Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon

Slice sampling normalized kernel-weighted completely random measure mixture models

Nicholas Foti, Sinead Williamson

The Lovász ϑ function, SVMs and finding large dense subgraphs

Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi

Semi-Supervised Domain Adaptation with Non-Parametric Copulas

David Lopez-paz, José M. Hernández-lobato, Bernhard Schölkopf

Mirror Descent Meets Fixed Share (and feels no regret)

Nicolò Cesa-bianchi, Pierre Gaillard, Gabor Lugosi, Gilles Stoltz

Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery

Ehsan Elhamifar, Guillermo Sapiro, René Vidal

Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models

Kei Wakabayashi, Takao Miura

Repulsive Mixtures

Francesca Petralia, Vinayak Rao, David B. Dunson

Isotropic Hashing

Weihao Kong, Wu-jun Li

Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction

Pietro D. Lena, Ken Nagata, Pierre F. Baldi

On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes

Bruno Scherrer, Boris Lesner

Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence

Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric

Trajectory-Based Short-Sighted Probabilistic Planning

Felipe Trevizan, Manuela Veloso

Hierarchical Optimistic Region Selection driven by Curiosity

Odalric-ambrym Maillard

Learning as MAP Inference in Discrete Graphical Models

Xianghang Liu, James Petterson, Tibério S. Caetano

Learned Prioritization for Trading Off Accuracy and Speed

Jiarong Jiang, Adam Teichert, Jason Eisner, Hal Daume

Multiresolution analysis on the symmetric group

Risi Kondor, Walter Dempsey

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction

Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim

Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity

Angela Eigenstetter, Bjorn Ommer

Delay Compensation with Dynamical Synapses

Chi Fung, K. Wong, Si Wu

Probabilistic n-Choose-k Models for Classification and Ranking

Kevin Swersky, Brendan J. Frey, Daniel Tarlow, Richard S. Zemel, Ryan P. Adams

Non-parametric Approximate Dynamic Programming via the Kernel Method

Nikhil Bhat, Vivek Farias, Ciamac C. Moallemi

Scalable imputation of genetic data with a discrete fragmentation-coagulation process

Lloyd Elliott, Yee W. Teh

Gradient-based kernel method for feature extraction and variable selection

Kenji Fukumizu, Chenlei Leng

Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning

Ulugbek Kamilov, Sundeep Rangan, Michael Unser, Alyson K. Fletcher

Risk-Aversion in Multi-armed Bandits

Amir Sani, Alessandro Lazaric, Rémi Munos

3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model

Sanja Fidler, Sven Dickinson, Raquel Urtasun

Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes

Michael Bryant, Erik B. Sudderth

Burn-in, bias, and the rationality of anchoring

Falk Lieder, Tom Griffiths, Noah Goodman

Multiresolution Gaussian Processes

Emily B. Fox, David B. Dunson

Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand

Amy Greenwald, Jiacui Li, Eric Sodomka

Accuracy at the Top

Stephen Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic

GenDeR: A Generic Diversified Ranking Algorithm

Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw Szymanski

Bayesian nonparametric models for ranked data

Francois Caron, Yee W. Teh

Scalable nonconvex inexact proximal splitting

Suvrit Sra

The variational hierarchical EM algorithm for clustering hidden Markov models

Emanuele Coviello, Gert R. Lanckriet, Antoni B. Chan

Semi-supervised Eigenvectors for Locally-biased Learning

Toke Hansen, Michael W. Mahoney

A Better Way to Pretrain Deep Boltzmann Machines

Geoffrey E. Hinton, Ruslan Salakhutdinov

On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks

Qirong Ho, Junming Yin, Eric P. Xing

Tight Bounds on Profile Redundancy and Distinguishability

Jayadev Acharya, Hirakendu Das, Alon Orlitsky

Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization

Demba Ba, Behtash Babadi, Patrick Purdon, Emery Brown

Learning to Discover Social Circles in Ego Networks

Jure Leskovec, Julian J. Mcauley

On the Sample Complexity of Robust PCA

Matthew Coudron, Gilad Lerman

Fused sparsity and robust estimation for linear models with unknown variance

Arnak Dalalyan, Yin Chen

Cocktail Party Processing via Structured Prediction

Yuxuan Wang, Deliang Wang

MAP Inference in Chains using Column Generation

David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum