NeurIPS 2011

306 papers

An Application of Tree-Structured Expectation Propagation for Channel Decoding

Pablo M. Olmos, Luis Salamanca, Juan Fuentes, Fernando Pérez-Cruz

Heavy-tailed Distances for Gradient Based Image Descriptors

Yangqing Jia, Trevor Darrell

ShareBoost: Efficient multiclass learning with feature sharing

Shai Shalev-shwartz, Yonatan Wexler, Amnon Shashua

Kernel Bayes' Rule

Kenji Fukumizu, Le Song, Arthur Gretton

A More Powerful Two-Sample Test in High Dimensions using Random Projection

Miles Lopes, Laurent Jacob, Martin J. Wainwright

Message-Passing for Approximate MAP Inference with Latent Variables

Jiarong Jiang, Piyush Rai, Hal Daume

Fast and Accurate k-means For Large Datasets

Michael Shindler, Alex Wong, Adam W. Meyerson

Optimal learning rates for least squares SVMs using Gaussian kernels

Mona Eberts, Ingo Steinwart

High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions

Animashree Anandkumar, Vincent Tan, Alan S. Willsky

Orthogonal Matching Pursuit with Replacement

Prateek Jain, Ambuj Tewari, Inderjit S Dhillon, Inderjit S. Dhillon

Sparse Bayesian Multi-Task Learning

Shengbo Guo, Onno Zoeter, Cédric Archambeau

A Collaborative Mechanism for Crowdsourcing Prediction Problems

Jacob D. Abernethy, Rafael M. Frongillo

Additive Gaussian Processes

David K. Duvenaud, Hannes Nickisch, Carl E. Rasmussen

Agnostic Selective Classification

Yair Wiener, Ran El-Yaniv

Hierarchically Supervised Latent Dirichlet Allocation

Adler J. Perotte, Frank Wood, Noemie Elhadad, Nicholas Bartlett

Autonomous Learning of Action Models for Planning

Neville Mehta, Prasad Tadepalli, Alan Fern

Variance Penalizing AdaBoost

Pannagadatta K. Shivaswamy, Tony Jebara

Extracting Speaker-Specific Information with a Regularized Siamese Deep Network

Ke Chen, Ahmad Salman

A Non-Parametric Approach to Dynamic Programming

Oliver B. Kroemer, Jan R. Peters

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning

Eric Moulines, Francis R. Bach

History distribution matching method for predicting effectiveness of HIV combination therapies

Jasmina Bogojeska

Spatial distance dependent Chinese restaurant processes for image segmentation

Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei

Efficient Online Learning via Randomized Rounding

Nicolò Cesa-bianchi, Ohad Shamir

Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries

Zhen J. Xiang, Hao Xu, Peter J. Ramadge

MAP Inference for Bayesian Inverse Reinforcement Learning

Jaedeug Choi, Kee-eung Kim

Data Skeletonization via Reeb Graphs

Xiaoyin Ge, Issam I. Safa, Mikhail Belkin, Yusu Wang

Budgeted Optimization with Concurrent Stochastic-Duration Experiments

Javad Azimi, Alan Fern, Xiaoli Z. Fern

Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss

Joseph Keshet, David A. McAllester

A Denoising View of Matrix Completion

Weiran Wang, Miguel Á. Carreira-Perpiñán, Zhengdong Lu

Complexity of Inference in Latent Dirichlet Allocation

David Sontag, Dan Roy

RTRMC: A Riemannian trust-region method for low-rank matrix completion

Nicolas Boumal, Pierre-antoine Absil

Dimensionality Reduction Using the Sparse Linear Model

Ioannis A. Gkioulekas, Todd Zickler

Bayesian Partitioning of Large-Scale Distance Data

David Adametz, Volker Roth

Neural Reconstruction with Approximate Message Passing (NeuRAMP)

Alyson K. Fletcher, Sundeep Rangan, Lav R. Varshney, Aniruddha Bhargava

Learning Eigenvectors for Free

Wouter M. Koolen, Wojciech Kotlowski, Manfred K. Warmuth

Linear Submodular Bandits and their Application to Diversified Retrieval

Yisong Yue, Carlos Guestrin

Trace Lasso: a trace norm regularization for correlated designs

Edouard Grave, Guillaume R. Obozinski, Francis R. Bach

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection

Richard Socher, Eric H. Huang, Jeffrey Pennin, Christopher D. Manning, Andrew Y. Ng

Image Parsing with Stochastic Scene Grammar

Yibiao Zhao, Song-chun Zhu

A concave regularization technique for sparse mixture models

Martin O. Larsson, Johan Ugander

Co-regularized Multi-view Spectral Clustering

Abhishek Kumar, Piyush Rai, Hal Daume

Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression

Sham M. Kakade, Varun Kanade, Ohad Shamir, Adam Kalai

Active Classification based on Value of Classifier

Tianshi Gao, Daphne Koller

Approximating Semidefinite Programs in Sublinear Time

Dan Garber, Elad Hazan

Dynamical segmentation of single trials from population neural data

Biljana Petreska, Byron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen I. Ryu

Testing a Bayesian Measure of Representativeness Using a Large Image Database

Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation

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

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance

Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf, Peter V. Gehler

Scalable Training of Mixture Models via Coresets

Dan Feldman, Matthew Faulkner, Andreas Krause

Composite Multiclass Losses

Elodie Vernet, Mark D. Reid, Robert C. Williamson

Multiclass Boosting: Theory and Algorithms

Mohammad J. Saberian, Nuno Vasconcelos

Structure Learning for Optimization

Shulin Yang, Ali Rahimi

Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints

Omar Z. Khan, Pascal Poupart, John-mark M. Agosta

Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories

Cristina Savin, Peter Dayan, Máté Lengyel

Understanding the Intrinsic Memorability of Images

Phillip Isola, Devi Parikh, Antonio Torralba, Aude Oliva

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm

Julie Dethier, Paul Nuyujukian, Chris Eliasmith, Terrence C. Stewart, Shauki A. Elasaad

Metric Learning with Multiple Kernels

Jun Wang, Huyen T. Do, Adam Woznica, Alexandros Kalousis

Ranking annotators for crowdsourced labeling tasks

Vikas C. Raykar, Shipeng Yu

Learning Anchor Planes for Classification

Ziming Zhang, Lubor Ladicky, Philip Torr, Amir Saffari

Sparse Recovery with Brownian Sensing

Alexandra Carpentier, Odalric-ambrym Maillard, Rémi Munos

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning

Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng, Quoc V Le, Quoc V. Le

Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Benjamin Recht, Christopher Re, Stephen Wright, Feng Niu

Query-Aware MCMC

Michael L. Wick, Andrew McCallum

Spectral Methods for Learning Multivariate Latent Tree Structure

Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song

Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning

Joni K. Pajarinen, Jaakko Peltonen

Policy Gradient Coagent Networks

Philip S. Thomas

Evaluating the inverse decision-making approach to preference learning

Alan Jern, Christopher G. Lucas, Charles Kemp

Active Learning with a Drifting Distribution

Liu Yang

Analytical Results for the Error in Filtering of Gaussian Processes

Alex K. Susemihl, Ron Meir, Manfred Opper

Why The Brain Separates Face Recognition From Object Recognition

Joel Z. Leibo, Jim Mutch, Tomaso Poggio

Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts

Matthias Hein, Simon Setzer

Sparse Filtering

Jiquan Ngiam, Zhenghao Chen, Sonia A. Bhaskar, Pang W. Koh, Andrew Y. Ng

Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation

Zhouchen Lin, Risheng Liu, Zhixun Su

PiCoDes: Learning a Compact Code for Novel-Category Recognition

Alessandro Bergamo, Lorenzo Torresani, Andrew W. Fitzgibbon

Video Annotation and Tracking with Active Learning

Carl Vondrick, Deva Ramanan

Convergent Bounds on the Euclidean Distance

Yoonho Hwang, Hee-kap Ahn

Nearest Neighbor based Greedy Coordinate Descent

Ambuj Tewari, Inderjit S Dhillon, Pradeep K Ravikumar, Inderjit S. Dhillon, Pradeep K. Ravikumar

Large-Scale Sparse Principal Component Analysis with Application to Text Data

Youwei Zhang, Laurent E. Ghaoui

Multilinear Subspace Regression: An Orthogonal Tensor Decomposition Approach

Qibin Zhao, Cesar F. Caiafa, Danilo P. Mandic, Liqing Zhang, Tonio Ball

Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons

Yan Karklin, Eero P. Simoncelli

Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals

Zuoguan Wang, Gerwin Schalk, Qiang Ji

Maximum Margin Multi-Instance Learning

Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Ding

Prediction strategies without loss

Michael Kapralov, Rina Panigrahy

Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors

Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos

SpaRCS: Recovering low-rank and sparse matrices from compressive measurements

Andrew E. Waters, Aswin C. Sankaranarayanan, Richard Baraniuk

Generalized Lasso based Approximation of Sparse Coding for Visual Recognition

Nobuyuki Morioka, Shin'ichi Satoh

The Doubly Correlated Nonparametric Topic Model

Dae I. Kim, Erik B. Sudderth

Regularized Laplacian Estimation and Fast Eigenvector Approximation

Patrick O. Perry, Michael W. Mahoney

The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers

Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference

David Wingate, Noah Goodman, Andreas Stuhlmueller, Jeffrey M. Siskind

Active learning of neural response functions with Gaussian processes

Mijung Park, Greg Horwitz, Jonathan W Pillow, Jonathan W. Pillow

Hashing Algorithms for Large-Scale Learning

Ping Li, Anshumali Shrivastava, Joshua L. Moore, Arnd C. König

On the Analysis of Multi-Channel Neural Spike Data

Bo Chen, Lawrence Carin, David E Carlson, David E. Carlson

Phase transition in the family of p-resistances

Morteza Alamgir, Ulrike V. Luxburg

Bayesian Bias Mitigation for Crowdsourcing

Fabian L. Wauthier, Michael I. Jordan

Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations

Emin Orhan, Robert A. Jacobs

Rapid Deformable Object Detection using Dual-Tree Branch-and-Bound

Iasonas Kokkinos

Variational Learning for Recurrent Spiking Networks

Danilo J. Rezende, Daan Wierstra, Wulfram Gerstner

k-NN Regression Adapts to Local Intrinsic Dimension

Samory Kpotufe

Lower Bounds for Passive and Active Learning

Maxim Raginsky, Alexander Rakhlin