Book

Emergence of Multiplication in a Biophysical Model of a Wide-Field Visual Neuron for Computing Object Approaches: Dynamics, Peaks, & Fits Matthias S. Keil

Action-Gap Phenomenon in Reinforcement Learning Amir-massoud Farahmand

Learning Higher-Order Graph Structure with Features by Structure Penalty Shilin Ding, Grace Wahba, Xiaojin Zhu

Efficient Methods for Overlapping Group Lasso Lei Yuan, Jun Liu, Jieping Ye

Priors over Recurrent Continuous Time Processes Ardavan Saeedi, Alexandre Bouchard-côté

The Kernel Beta Process Lu Ren, Yingjian Wang, Lawrence Carin, David B. Dunson

Lower Bounds for Passive and Active Learning Maxim Raginsky, Alexander Rakhlin

k-NN Regression Adapts to Local Intrinsic Dimension Samory Kpotufe

Variational Learning for Recurrent Spiking Networks Danilo J. Rezende, Daan Wierstra, Wulfram Gerstner

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

Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations Emin Orhan, Robert A. Jacobs

Bayesian Bias Mitigation for Crowdsourcing Fabian L. Wauthier, Michael I. Jordan

Phase transition in the family of p-resistances Morteza Alamgir, Ulrike V. Luxburg

On the Analysis of Multi-Channel Neural Spike Data Bo Chen, David E. Carlson, Lawrence Carin

Hashing Algorithms for Large-Scale Learning Ping Li, Anshumali Shrivastava, Joshua L. Moore, Arnd C. König

Active learning of neural response functions with Gaussian processes Mijung Park, Greg Horwitz, Jonathan W. Pillow

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference David Wingate, Noah Goodman, Andreas Stuhlmueller, Jeffrey M. Siskind

The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella

Regularized Laplacian Estimation and Fast Eigenvector Approximation Patrick O. Perry, Michael W. Mahoney

The Doubly Correlated Nonparametric Topic Model Dae I. Kim, Erik B. Sudderth

Generalized Lasso based Approximation of Sparse Coding for Visual Recognition Nobuyuki Morioka, Shin'ichi Satoh

SpaRCS: Recovering low-rank and sparse matrices from compressive measurements Andrew E. Waters, Aswin C. Sankaranarayanan, Richard Baraniuk

Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos

Prediction strategies without loss Michael Kapralov, Rina Panigrahy

Maximum Margin Multi-Instance Learning Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Ding

Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals Zuoguan Wang, Gerwin Schalk, Qiang Ji

Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons Yan Karklin, Eero P. Simoncelli

Multilinear Subspace Regression: An Orthogonal Tensor Decomposition Approach Qibin Zhao, Cesar F. Caiafa, Danilo P. Mandic, Liqing Zhang, Tonio Ball, Andreas Schulze-bonhage, Andrzej S. Cichocki

Large-Scale Sparse Principal Component Analysis with Application to Text Data Youwei Zhang, Laurent E. Ghaoui

Nearest Neighbor based Greedy Coordinate Descent Inderjit S. Dhillon, Pradeep K. Ravikumar, Ambuj Tewari

Convergent Bounds on the Euclidean Distance Yoonho Hwang, Hee-kap Ahn

Video Annotation and Tracking with Active Learning Carl Vondrick, Deva Ramanan

PiCoDes: Learning a Compact Code for Novel-Category Recognition Alessandro Bergamo, Lorenzo Torresani, Andrew W. Fitzgibbon

Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation Zhouchen Lin, Risheng Liu, Zhixun Su

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

Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts Matthias Hein, Simon Setzer

Why The Brain Separates Face Recognition From Object Recognition Joel Z. Leibo, Jim Mutch, Tomaso Poggio

Analytical Results for the Error in Filtering of Gaussian Processes Alex K. Susemihl, Ron Meir, Manfred Opper

Active Learning with a Drifting Distribution Liu Yang

Evaluating the inverse decision-making approach to preference learning Alan Jern, Christopher G. Lucas, Charles Kemp

Policy Gradient Coagent Networks Philip S. Thomas

Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning Joni K. Pajarinen, Jaakko Peltonen

Spectral Methods for Learning Multivariate Latent Tree Structure Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang

Query-Aware MCMC Michael L. Wick, Andrew McCallum

Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Benjamin Recht, Christopher Re, Stephen Wright, Feng Niu

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng

Sparse Recovery with Brownian Sensing Alexandra Carpentier, Odalric-ambrym Maillard, Rémi Munos

Learning Anchor Planes for Classification Ziming Zhang, Lubor Ladicky, Philip Torr, Amir Saffari

Ranking annotators for crowdsourced labeling tasks Vikas C. Raykar, Shipeng Yu

Metric Learning with Multiple Kernels Jun Wang, Huyen T. Do, Adam Woznica, Alexandros Kalousis

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, Krishna V. Shenoy, Kwabena A. Boahen

Understanding the Intrinsic Memorability of Images Phillip Isola, Devi Parikh, Antonio Torralba, Aude Oliva

Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories Cristina Savin, Peter Dayan, Máté Lengyel

Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints Omar Z. Khan, Pascal Poupart, John-mark M. Agosta

Structure Learning for Optimization Shulin Yang, Ali Rahimi

Multiclass Boosting: Theory and Algorithms Mohammad J. Saberian, Nuno Vasconcelos

Composite Multiclass Losses Elodie Vernet, Mark D. Reid, Robert C. Williamson

Scalable Training of Mixture Models via Coresets Dan Feldman, Matthew Faulkner, Andreas Krause

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf, Peter V. Gehler

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar, Mátyás A. Sustik

Testing a Bayesian Measure of Representativeness Using a Large Image Database Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths

Dynamical segmentation of single trials from population neural data Biljana Petreska, Byron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani

Approximating Semidefinite Programs in Sublinear Time Dan Garber, Elad Hazan

Active Classification based on Value of Classifier Tianshi Gao, Daphne Koller

Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression Sham M. Kakade, Varun Kanade, Ohad Shamir, Adam Kalai

Co-regularized Multi-view Spectral Clustering Abhishek Kumar, Piyush Rai, Hal Daume

A concave regularization technique for sparse mixture models Martin O. Larsson, Johan Ugander

Image Parsing with Stochastic Scene Grammar Yibiao Zhao, Song-chun Zhu

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection Richard Socher, Eric H. Huang, Jeffrey Pennin, Christopher D. Manning, Andrew Y. Ng

Trace Lasso: a trace norm regularization for correlated designs Edouard Grave, Guillaume R. Obozinski, Francis R. Bach

Linear Submodular Bandits and their Application to Diversified Retrieval Yisong Yue, Carlos Guestrin

Learning Eigenvectors for Free Wouter M. Koolen, Wojciech Kotlowski, Manfred K. Warmuth

Neural Reconstruction with Approximate Message Passing (NeuRAMP) Alyson K. Fletcher, Sundeep Rangan, Lav R. Varshney, Aniruddha Bhargava

Bayesian Partitioning of Large-Scale Distance Data David Adametz, Volker Roth

Dimensionality Reduction Using the Sparse Linear Model Ioannis A. Gkioulekas, Todd Zickler

RTRMC: A Riemannian trust-region method for low-rank matrix completion Nicolas Boumal, Pierre-antoine Absil

Complexity of Inference in Latent Dirichlet Allocation David Sontag, Dan Roy

A Denoising View of Matrix Completion Weiran Wang, Miguel Á. Carreira-Perpiñán, Zhengdong Lu

Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss Joseph Keshet, David A. McAllester

Budgeted Optimization with Concurrent Stochastic-Duration Experiments Javad Azimi, Alan Fern, Xiaoli Z. Fern

Data Skeletonization via Reeb Graphs Xiaoyin Ge, Issam I. Safa, Mikhail Belkin, Yusu Wang

MAP Inference for Bayesian Inverse Reinforcement Learning Jaedeug Choi, Kee-eung Kim

Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries Zhen J. Xiang, Hao Xu, Peter J. Ramadge

Efficient Online Learning via Randomized Rounding Nicolò Cesa-bianchi, Ohad Shamir

Spatial distance dependent Chinese restaurant processes for image segmentation Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei

History distribution matching method for predicting effectiveness of HIV combination therapies Jasmina Bogojeska

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning Eric Moulines, Francis R. Bach

A Non-Parametric Approach to Dynamic Programming Oliver B. Kroemer, Jan R. Peters

Extracting Speaker-Specific Information with a Regularized Siamese Deep Network Ke Chen, Ahmad Salman

Variance Penalizing AdaBoost Pannagadatta K. Shivaswamy, Tony Jebara

Autonomous Learning of Action Models for Planning Neville Mehta, Prasad Tadepalli, Alan Fern

Hierarchically Supervised Latent Dirichlet Allocation Adler J. Perotte, Frank Wood, Noemie Elhadad, Nicholas Bartlett

Agnostic Selective Classification Yair Wiener, Ran El-Yaniv

Additive Gaussian Processes David K. Duvenaud, Hannes Nickisch, Carl E. Rasmussen

A Collaborative Mechanism for Crowdsourcing Prediction Problems Jacob D. Abernethy, Rafael M. Frongillo

Sparse Bayesian Multi-Task Learning Shengbo Guo, Onno Zoeter, Cédric Archambeau

Orthogonal Matching Pursuit with Replacement Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon

High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions Animashree Anandkumar, Vincent Tan, Alan S. Willsky

Optimal learning rates for least squares SVMs using Gaussian kernels Mona Eberts, Ingo Steinwart

Fast and Accurate k-means For Large Datasets Michael Shindler, Alex Wong, Adam W. Meyerson

Message-Passing for Approximate MAP Inference with Latent Variables Jiarong Jiang, Piyush Rai, Hal Daume

A More Powerful Two-Sample Test in High Dimensions using Random Projection Miles Lopes, Laurent Jacob, Martin J. Wainwright

Kernel Bayes' Rule Kenji Fukumizu, Le Song, Arthur Gretton

ShareBoost: Efficient multiclass learning with feature sharing Shai Shalev-shwartz, Yonatan Wexler, Amnon Shashua

Heavy-tailed Distances for Gradient Based Image Descriptors Yangqing Jia, Trevor Darrell

An Application of Tree-Structured Expectation Propagation for Channel Decoding Pablo M. Olmos, Luis Salamanca, Juan Fuentes, Fernando Pérez-Cruz

PAC-Bayesian Analysis of Contextual Bandits Yevgeny Seldin, Peter Auer, John S. Shawe-taylor, Ronald Ortner, François Laviolette

Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition Jia Deng, Sanjeev Satheesh, Alexander C. Berg, Fei Li

Divide-and-Conquer Matrix Factorization Lester W. Mackey, Michael I. Jordan, Ameet Talwalkar

Non-conjugate Variational Message Passing for Multinomial and Binary Regression David A. Knowles, Tom Minka

Im2Text: Describing Images Using 1 Million Captioned Photographs Vicente Ordonez, Girish Kulkarni, Tamara L. Berg

Modelling Genetic Variations using Fragmentation-Coagulation Processes Yee W. Teh, Charles Blundell, Lloyd Elliott

Uniqueness of Belief Propagation on Signed Graphs Yusuke Watanabe

Improving Topic Coherence with Regularized Topic Models David Newman, Edwin V. Bonilla, Wray Buntine

Beating SGD: Learning SVMs in Sublinear Time Elad Hazan, Tomer Koren, Nati Srebro

Inferring spike-timing-dependent plasticity from spike train data Ian Stevenson, Konrad Koerding

Bayesian Spike-Triggered Covariance Analysis Ill Memming Park, Jonathan W. Pillow

Adaptive Hedge Tim V. Erven, Wouter M. Koolen, Steven D. Rooij, Peter Grünwald

Matrix Completion for Multi-label Image Classification Ricardo S. Cabral, Fernando Torre, Joao P. Costeira, Alexandre Bernardino

Continuous-Time Regression Models for Longitudinal Networks Duy Q. Vu, David Hunter, Padhraic Smyth, Arthur U. Asuncion

Stochastic convex optimization with bandit feedback Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin

Online Learning: Stochastic, Constrained, and Smoothed Adversaries Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari

Similarity-based Learning via Data Driven Embeddings Purushottam Kar, Prateek Jain

Maximum Margin Multi-Label Structured Prediction Christoph H. Lampert

Active Ranking using Pairwise Comparisons Kevin G. Jamieson, Robert Nowak

Selecting Receptive Fields in Deep Networks Adam Coates, Andrew Y. Ng

Learning Auto-regressive Models from Sequence and Non-sequence Data Tzu-kuo Huang, Jeff G. Schneider

Multi-View Learning of Word Embeddings via CCA Paramveer Dhillon, Dean P. Foster, Lyle H. Ungar

Projection onto A Nonnegative Max-Heap Jun Liu, Liang Sun, Jieping Ye

Learning to Learn with Compound HD Models Antonio Torralba, Joshua B. Tenenbaum, Ruslan Salakhutdinov

Object Detection with Grammar Models Ross B. Girshick, Pedro F. Felzenszwalb, David A. McAllester

Inductive reasoning about chimeric creatures Charles Kemp

Empirical models of spiking in neural populations Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

An Exact Algorithm for F-Measure Maximization Krzysztof J. Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier

Exploiting spatial overlap to efficiently compute appearance distances between image windows Bogdan Alexe, Viviana Petrescu, Vittorio Ferrari

Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment Sebastian A. Kurtek, Anuj Srivastava, Wei Wu

Multi-armed bandits on implicit metric spaces Aleksandrs Slivkins

Predicting response time and error rates in visual search Bo Chen, Vidhya Navalpakkam, Pietro Perona

Sequence learning with hidden units in spiking neural networks Johanni Brea, Walter Senn, Jean-pascal Pfister

Convergent Fitted Value Iteration with Linear Function Approximation Daniel J. Lizotte

Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint Kenji Fukumizu, Gert R. Lanckriet, Bharath K. Sriperumbudur

Predicting Dynamic Difficulty Olana Missura, Thomas Gärtner

Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness Rémi Munos

Robust Multi-Class Gaussian Process Classification Daniel Hernández-lobato, Jose M. Hernández-lobato, Pierre Dupont

Practical Variational Inference for Neural Networks Alex Graves

Penalty Decomposition Methods for Rank Minimization Yong Zhang, Zhaosong Lu

Accelerated Adaptive Markov Chain for Partition Function Computation Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman

On Strategy Stitching in Large Extensive Form Multiplayer Games Richard G. Gibson, Duane Szafron

Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity Nir Ailon

Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation Onur Dikmen, Cédric Févotte

From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models Skander Mensi, Richard Naud, Wulfram Gerstner

Generalised Coupled Tensor Factorisation Kenan Y. Yılmaz, Ali T. Cemgil, Umut Simsekli

Prismatic Algorithm for Discrete D.C. Programming Problem Yoshinobu Kawahara, Takashi Washio

On the Completeness of First-Order Knowledge Compilation for Lifted Probabilistic Inference Guy Broeck

Analysis and Improvement of Policy Gradient Estimation Tingting Zhao, Hirotaka Hachiya, Gang Niu, Masashi Sugiyama

On Tracking The Partition Function Guillaume Desjardins, Yoshua Bengio, Aaron C. Courville

Portmanteau Vocabularies for Multi-Cue Image Representation Fahad S. Khan, Joost Weijer, Andrew D. Bagdanov, Maria Vanrell

Algorithms for Hyper-Parameter Optimization James S. Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl

Finite Time Analysis of Stratified Sampling for Monte Carlo Alexandra Carpentier, Rémi Munos

Online Submodular Set Cover, Ranking, and Repeated Active Learning Andrew Guillory, Jeff A. Bilmes

The Fast Convergence of Boosting Matus J. Telgarsky

See the Tree Through the Lines: The Shazoo Algorithm Fabio Vitale, Nicolò Cesa-bianchi, Claudio Gentile, Giovanni Zappella

t-divergence Based Approximate Inference Nan Ding, Yuan Qi, S.v.n. Vishwanathan

Boosting with Maximum Adaptive Sampling Charles Dubout, Francois Fleuret

Inverting Grice's Maxims to Learn Rules from Natural Language Extractions Mohammad S. Sorower, Janardhan R. Doppa, Walker Orr, Prasad Tadepalli, Thomas G. Dietterich, Xiaoli Z. Fern

Efficient anomaly detection using bipartite k-NN graphs Kumar Sricharan, Alfred O. Hero

Shallow vs. Deep Sum-Product Networks Olivier Delalleau, Yoshua Bengio

Expressive Power and Approximation Errors of Restricted Boltzmann Machines Guido F. Montufar, Johannes Rauh, Nihat Ay

Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators Dominique C. Perrault-joncas, Marina Meila

Information Rates and Optimal Decoding in Large Neural Populations Kamiar R. Rad, Liam Paninski

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization Mark Schmidt, Nicolas L. Roux, Francis R. Bach

Co-Training for Domain Adaptation Minmin Chen, Kilian Q. Weinberger, John Blitzer

Learning to Agglomerate Superpixel Hierarchies Viren Jain, Srinivas C. Turaga, K Briggman, Moritz N. Helmstaedter, Winfried Denk, H. S. Seung

Structured Learning for Cell Tracking Xinghua Lou, Fred A. Hamprecht

Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices Xianxing Zhang, Lawrence Carin, David B. Dunson

Selecting the State-Representation in Reinforcement Learning Odalric-ambrym Maillard, Daniil Ryabko, Rémi Munos

A Reinforcement Learning Theory for Homeostatic Regulation Mehdi Keramati, Boris S. Gutkin

Semantic Labeling of 3D Point Clouds for Indoor Scenes Hema S. Koppula, Abhishek Anand, Thorsten Joachims, Ashutosh Saxena

Higher-Order Correlation Clustering for Image Segmentation Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, Chang D. Yoo

Learning large-margin halfspaces with more malicious noise Phil Long, Rocco Servedio

The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning Marius Kloft, Gilles Blanchard

A Global Structural EM Algorithm for a Model of Cancer Progression Ali Tofigh, Erik Sj̦lund, Mattias H̦glund, Jens Lagergren

Infinite Latent SVM for Classification and Multi-task Learning Jun Zhu, Ning Chen, Eric P. Xing

On U-processes and clustering performance Stéphan J. Clémençcon

Robust Lasso with missing and grossly corrupted observations Nasser M. Nasrabadi, Trac D. Tran, Nam Nguyen

Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction Siwei Lyu

Select and Sample - A Model of Efficient Neural Inference and Learning Jacquelyn A. Shelton, Abdul S. Sheikh, Pietro Berkes, Joerg Bornschein, Jörg Lücke

Clustered Multi-Task Learning Via Alternating Structure Optimization Jiayu Zhou, Jianhui Chen, Jieping Ye

On Learning Discrete Graphical Models using Greedy Methods Ali Jalali, Christopher C. Johnson, Pradeep K. Ravikumar

Learning person-object interactions for action recognition in still images Vincent Delaitre, Josef Sivic, Ivan Laptev

Efficient inference in matrix-variate Gaussian models with \iid observation noise Oliver Stegle, Christoph Lippert, Joris M. Mooij, Neil D. Lawrence, Karsten Borgwardt

Confidence Sets for Network Structure David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi

Structural equations and divisive normalization for energy-dependent component analysis Jun-ichiro Hirayama, Aapo Hyvärinen

Gaussian Process Training with Input Noise Andrew Mchutchon, Carl E. Rasmussen

On the Universality of Online Mirror Descent Nati Srebro, Karthik Sridharan, Ambuj Tewari

Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning Taiji Suzuki

Speedy Q-Learning Mohammad Ghavamzadeh, Hilbert J. Kappen, Mohammad G. Azar, Rémi Munos

High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity Po-ling Loh, Martin J. Wainwright

Greedy Model Averaging Dong Dai, Tong Zhang

Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation Nico Goernitz, Christian K. Widmer, Georg Zeller, Andre Kahles, Gunnar Rätsch, Sören Sonnenburg

Generalized Beta Mixtures of Gaussians Artin Armagan, Merlise Clyde, David B. Dunson

Variational Gaussian Process Dynamical Systems Andreas Damianou, Michalis K. Titsias, Neil D. Lawrence

Statistical Tests for Optimization Efficiency Levi Boyles, Anoop Korattikara, Deva Ramanan, Max Welling

Statistical Performance of Convex Tensor Decomposition Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima

A Machine Learning Approach to Predict Chemical Reactions Matthew A. Kayala, Pierre F. Baldi

Sparse Features for PCA-Like Linear Regression Christos Boutsidis, Petros Drineas, Malik Magdon-Ismail

Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning Michalis K. Titsias, Miguel Lázaro-Gredilla

Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability David P. Reichert, Peggy Series, Amos J. Storkey

Reinforcement Learning using Kernel-Based Stochastic Factorization Andre Barreto, Doina Precup, Joelle Pineau

Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter, Ohad Shamir, Nati Srebro, Karthik Sridharan

Generalizing from Several Related Classification Tasks to a New Unlabeled Sample Gilles Blanchard, Gyemin Lee, Clayton Scott

Energetically Optimal Action Potentials Martin B. Stemmler, Biswa Sengupta, Simon Laughlin, Jeremy Niven

Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent Shinichi Nakajima, Masashi Sugiyama, S. D. Babacan

Algorithms and hardness results for parallel large margin learning Phil Long, Rocco Servedio

Semi-supervised Regression via Parallel Field Regularization Binbin Lin, Chiyuan Zhang, Xiaofei He

Thinning Measurement Models and Questionnaire Design Ricardo Silva

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials Philipp Krähenbühl, Vladlen Koltun

Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC Trung T. Pham, Tat-jun Chin, Jin Yu, David Suter

Active dendrites: adaptation to spike-based communication Balazs B. Ujfalussy, Máté Lengyel

Shaping Level Sets with Submodular Functions Francis R. Bach

Probabilistic amplitude and frequency demodulation Richard Turner, Maneesh Sahani

Multi-Bandit Best Arm Identification Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck

Nonlinear Inverse Reinforcement Learning with Gaussian Processes Sergey Levine, Zoran Popovic, Vladlen Koltun

EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning Feng Yan, Yuan Qi

Iterative Learning for Reliable Crowdsourcing Systems David R. Karger, Sewoong Oh, Devavrat Shah

Minimax Localization of Structural Information in Large Noisy Matrices Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh

Crowdclustering Ryan G. Gomes, Peter Welinder, Andreas Krause, Pietro Perona

Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs Armen Allahverdyan, Aram Galstyan

Environmental statistics and the trade-off between model-based and TD learning in humans Dylan A. Simon, Nathaniel D. Daw

A Model for Temporal Dependencies in Event Streams Asela Gunawardana, Christopher Meek, Puyang Xu

Inferring Interaction Networks using the IBP applied to microRNA Target Prediction Hai-son P. Le, Ziv Bar-joseph

Learning unbelievable probabilities Zachary Pitkow, Yashar Ahmadian, Ken D. Miller

Relative Density-Ratio Estimation for Robust Distribution Comparison Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama

The Manifold Tangent Classifier Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller

Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds Nitesh Shroff, Pavan Turaga, Rama Chellappa

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines Matthew D. Zeiler, Graham W. Taylor, Leonid Sigal, Iain Matthews, Rob Fergus

Committing Bandits Loc X. Bui, Ramesh Johari, Shie Mannor

Large-Scale Category Structure Aware Image Categorization Bin Zhao, Fei Li, Eric P. Xing

On Causal Discovery with Cyclic Additive Noise Models Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf

Sparse recovery by thresholded non-negative least squares Martin Slawski, Matthias Hein

A Two-Stage Weighting Framework for Multi-Source Domain Adaptation Qian Sun, Rita Chattopadhyay, Sethuraman Panchanathan, Jieping Ye

Variance Reduction in Monte-Carlo Tree Search Joel Veness, Marc Lanctot, Michael Bowling

Advice Refinement in Knowledge-Based SVMs Gautam Kunapuli, Richard Maclin, Jude W. Shavlik

On fast approximate submodular minimization Stefanie Jegelka, Hui Lin, Jeff A. Bilmes

Multiple Instance Filtering Kamil A. Wnuk, Stefano Soatto

A reinterpretation of the policy oscillation phenomenon in approximate policy iteration Paul Wagner

$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding Congcong Li, Ashutosh Saxena, Tsuhan Chen

Maximum Covariance Unfolding : Manifold Learning for Bimodal Data Vijay Mahadevan, Chi W. Wong, Jose C. Pereira, Tom Liu, Nuno Vasconcelos, Lawrence K. Saul

Noise Thresholds for Spectral Clustering Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh

Kernel Embeddings of Latent Tree Graphical Models Le Song, Eric P. Xing, Ankur P. Parikh

Learning a Distance Metric from a Network Blake Shaw, Bert Huang, Tony Jebara

Selective Prediction of Financial Trends with Hidden Markov Models Dmitry Pidan, Ran El-Yaniv

Blending Autonomous Exploration and Apprenticeship Learning Thomas J. Walsh, Daniel K. Hewlett, Clayton T. Morrison

Transfer Learning by Borrowing Examples for Multiclass Object Detection Joseph J. Lim, Ruslan Salakhutdinov, Antonio Torralba

A blind sparse deconvolution method for neural spike identification Chaitanya Ekanadham, Daniel Tranchina, Eero P. Simoncelli

Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery Scott Niekum, Andrew G. Barto

Unsupervised learning models of primary cortical receptive fields and receptive field plasticity Maneesh Bhand, Ritvik Mudur, Bipin Suresh, Andrew Saxe, Andrew Y. Ng

Improved Algorithms for Linear Stochastic Bandits Yasin Abbasi-yadkori, Dávid Pál, Csaba Szepesvári

From Bandits to Experts: On the Value of Side-Observations Shie Mannor, Ohad Shamir

Optimal Reinforcement Learning for Gaussian Systems Philipp Hennig

An Empirical Evaluation of Thompson Sampling Olivier Chapelle, Lihong Li

Efficient Offline Communication Policies for Factored Multiagent POMDPs João V. Messias, Matthijs Spaan, Pedro U. Lima

Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning Xinggang Wang, Xiang Bai, Xingwei Yang, Wenyu Liu, Longin J. Latecki

Quasi-Newton Methods for Markov Chain Monte Carlo Yichuan Zhang, Charles A. Sutton

Inference in continuous-time change-point models Florian Stimberg, Manfred Opper, Guido Sanguinetti, Andreas Ruttor

Universal low-rank matrix recovery from Pauli measurements Yi-kai Liu

A Convergence Analysis of Log-Linear Training Simon Wiesler, Hermann Ney

On the accuracy of l1-filtering of signals with block-sparse structure Fatma K. Karzan, Arkadi S. Nemirovski, Boris T. Polyak, Anatoli Juditsky

Group Anomaly Detection using Flexible Genre Models Liang Xiong, Barnabás Póczos, Jeff G. Schneider

Randomized Algorithms for Comparison-based Search Dominique Tschopp, Suhas Diggavi, Payam Delgosha, Soheil Mohajer

Multiple Instance Learning on Structured Data Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence

Probabilistic Joint Image Segmentation and Labeling Adrian Ion, Joao Carreira, Cristian Sminchisescu

Learning to Search Efficiently in High Dimensions Zhen Li, Huazhong Ning, Liangliang Cao, Tong Zhang, Yihong Gong, Thomas S. Huang

Learning a Tree of Metrics with Disjoint Visual Features Kristen Grauman, Fei Sha, Sung Ju Hwang

Monte Carlo Value Iteration with Macro-Actions Zhan Lim, Lee Sun, David Hsu

Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels Vikas Sindhwani, Aurelie C. Lozano

Distributed Delayed Stochastic Optimization Alekh Agarwal, John C. Duchi

An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments Michael Mozer, Benjamin Link, Harold Pashler

Contextual Gaussian Process Bandit Optimization Andreas Krause, Cheng S. Ong

Learning with the weighted trace-norm under arbitrary sampling distributions Rina Foygel, Ohad Shamir, Nati Srebro, Ruslan Salakhutdinov

Demixed Principal Component Analysis Wieland Brendel, Ranulfo Romo, Christian K. Machens

Reconstructing Patterns of Information Diffusion from Incomplete Observations Flavio Chierichetti, David Liben-nowell, Jon M. Kleinberg

Differentially Private M-Estimators Jing Lei

Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification Ichiro Takeuchi, Masashi Sugiyama

Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms Liefeng Bo, Xiaofeng Ren, Dieter Fox

Solving Decision Problems with Limited Information Denis D. Maua, Cassio Campos

How Do Humans Teach: On Curriculum Learning and Teaching Dimension Faisal Khan, Bilge Mutlu, Xiaojin Zhu

A rational model of causal inference with continuous causes Thomas L. Griffiths, Michael James

Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis Shuai Huang, Jing Li, Jieping Ye, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman

Structured sparse coding via lateral inhibition Arthur D. Szlam, Karol Gregor, Yann L. Cun

TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning George Konidaris, Scott Niekum, Philip S. Thomas

Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron Ryota Kobayashi, Yasuhiro Tsubo, Petr Lansky, Shigeru Shinomoto

Joint 3D Estimation of Objects and Scene Layout Andreas Geiger, Christian Wojek, Raquel Urtasun

Sparse Manifold Clustering and Embedding Ehsan Elhamifar, René Vidal

Submodular Multi-Label Learning James Petterson, Tibério S. Caetano

Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities Angela Yao, Juergen Gall, Luc V. Gool, Raquel Urtasun

Collective Graphical Models Daniel R. Sheldon, Thomas G. Dietterich

Sparse Estimation with Structured Dictionaries David P. Wipf

Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction Elad Hazan, Satyen Kale

The Fixed Points of Off-Policy TD J. Z. Kolter

Transfer from Multiple MDPs Alessandro Lazaric, Marcello Restelli

Pylon Model for Semantic Segmentation Victor Lempitsky, Andrea Vedaldi, Andrew Zisserman

How biased are maximum entropy models? Jakob H. Macke, Iain Murray, Peter E. Latham

Gaussian process modulated renewal processes Yee W. Teh, Vinayak Rao

An ideal observer model for identifying the reference frame of objects Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths

Greedy Algorithms for Structurally Constrained High Dimensional Problems Ambuj Tewari, Pradeep K. Ravikumar, Inderjit S. Dhillon

Advances in Neural Information Processing Systems 24 (NIPS 2011)

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