Advances in Neural Information Processing Systems 23

NIPS 2010

Edited by J. Lafferty and C. Williams and J. Shawe-Taylor and R. Zemel and A. Culotta

ISBN: 9781617823800

292 papers

Agnostic Active Learning Without Constraints Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang
A Dirty Model for Multi-task Learning Ali Jalali, Sujay Sanghavi, Chao Ruan, Pradeep K. Ravikumar
Generative Local Metric Learning for Nearest Neighbor Classification Yung-kyun Noh, Byoung-tak Zhang, Daniel D. Lee
Relaxed Clipping: A Global Training Method for Robust Regression and Classification Min Yang, Linli Xu, Martha White, Dale Schuurmans, Yao-liang Yu
Linear readout from a neural population with partial correlation data Adrien Wohrer, Ranulfo Romo, Christian K. Machens
On Herding and the Perceptron Cycling Theorem Andrew Gelfand, Yutian Chen, Laurens Maaten, Max Welling
Tiled convolutional neural networks Jiquan Ngiam, Zhenghao Chen, Daniel Chia, Pang W. Koh, Quoc V. Le, Andrew Y. Ng
Decomposing Isotonic Regression for Efficiently Solving Large Problems Ronny Luss, Saharon Rosset, Moni Shahar
Learning Kernels with Radiuses of Minimum Enclosing Balls Kun Gai, Guangyun Chen, Chang-shui Zhang
Label Embedding Trees for Large Multi-Class Tasks Samy Bengio, Jason Weston, David Grangier
Deep Coding Network Yuanqing Lin, Tong Zhang, Shenghuo Zhu, Kai Yu
Transduction with Matrix Completion: Three Birds with One Stone Andrew Goldberg, Ben Recht, Junming Xu, Robert Nowak, Xiaojin Zhu
Extended Bayesian Information Criteria for Gaussian Graphical Models Rina Foygel, Mathias Drton
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces Abhinav Gupta, Martial Hebert, Takeo Kanade, David M. Blei
A Computational Decision Theory for Interactive Assistants Alan Fern, Prasad Tadepalli
Large Margin Multi-Task Metric Learning Shibin Parameswaran, Kilian Q. Weinberger
Evaluating neuronal codes for inference using Fisher information Haefner Ralf, Matthias Bethge
Guaranteed Rank Minimization via Singular Value Projection Prateek Jain, Raghu Meka, Inderjit S. Dhillon
Double Q-learning Hado V. Hasselt
Generalized roof duality and bisubmodular functions Vladimir Kolmogorov
Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization Feiping Nie, Heng Huang, Xiao Cai, Chris H. Ding
Repeated Games against Budgeted Adversaries Jacob D. Abernethy, Manfred K. Warmuth
Switching state space model for simultaneously estimating state transitions and nonstationary firing rates Ken Takiyama, Masato Okada
Why are some word orders more common than others? A uniform information density account Luke Maurits, Dan Navarro, Amy Perfors
Getting lost in space: Large sample analysis of the resistance distance Ulrike V. Luxburg, Agnes Radl, Matthias Hein
Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers Manas Pathak, Shantanu Rane, Bhiksha Raj
Convex Multiple-Instance Learning by Estimating Likelihood Ratio Fuxin Li, Cristian Sminchisescu
Short-term memory in neuronal networks through dynamical compressed sensing Surya Ganguli, Haim Sompolinsky
The Multidimensional Wisdom of Crowds Peter Welinder, Steve Branson, Pietro Perona, Serge J. Belongie
Boosting Classifier Cascades Nuno Vasconcelos, Mohammad J. Saberian
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation Mathieu Salzmann, Raquel Urtasun
Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks Kentaro Katahira, Kazuo Okanoya, Masato Okada
Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains Martha White, Adam White
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification Li-jia Li, Hao Su, Li Fei-fei, Eric P. Xing
Using body-anchored priors for identifying actions in single images Leonid Karlinsky, Michael Dinerstein, Shimon Ullman
Reward Design via Online Gradient Ascent Jonathan Sorg, Richard L. Lewis, Satinder P. Singh
Universal Consistency of Multi-Class Support Vector Classification Tobias Glasmachers
Supervised Clustering Pranjal Awasthi, Reza B. Zadeh
Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics Kanaka Rajan, L Abbott, Haim Sompolinsky
Distributionally Robust Markov Decision Processes Huan Xu, Shie Mannor
Empirical Risk Minimization with Approximations of Probabilistic Grammars Noah A. Smith, Shay B. Cohen
MAP Estimation for Graphical Models by Likelihood Maximization Akshat Kumar, Shlomo Zilberstein
Identifying graph-structured activation patterns in networks James Sharpnack, Aarti Singh
Size Matters: Metric Visual Search Constraints from Monocular Metadata Mario Fritz, Kate Saenko, Trevor Darrell
Near-Optimal Bayesian Active Learning with Noisy Observations Daniel Golovin, Andreas Krause, Debajyoti Ray
Probabilistic Belief Revision with Structural Constraints Peter Jones, Venkatesh Saligrama, Sanjoy Mitter
Structured Determinantal Point Processes Alex Kulesza, Ben Taskar
b-Bit Minwise Hashing for Estimating Three-Way Similarities Ping Li, Arnd Konig, Wenhao Gui
Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike Stella X. Yu
Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting Chris Barber, Joseph Bockhorst, Paul Roebber
Link Discovery using Graph Feature Tracking Emile Richard, Nicolas Baskiotis, Theodoros Evgeniou, Nicolas Vayatis
A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model Sebastian Millner, Andreas Grübl, Karlheinz Meier, Johannes Schemmel, Marc-olivier Schwartz
Sparse Inverse Covariance Selection via Alternating Linearization Methods Katya Scheinberg, Shiqian Ma, Donald Goldfarb
Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories George Konidaris, Scott Kuindersma, Roderic Grupen, Andrew G. Barto
Trading off Mistakes and Don't-Know Predictions Amin Sayedi, Morteza Zadimoghaddam, Avrim Blum
Evaluation of Rarity of Fingerprints in Forensics Chang Su, Sargur Srihari
(RF)^2 -- Random Forest Random Field Nadia Payet, Sinisa Todorovic
Online Learning in The Manifold of Low-Rank Matrices Uri Shalit, Daphna Weinshall, Gal Chechik
Variational bounds for mixed-data factor analysis Mohammad Emtiyaz Khan, Guillaume Bouchard, Kevin P. Murphy, Benjamin M. Marlin
Copula Bayesian Networks Gal Elidan
Evidence-Specific Structures for Rich Tractable CRFs Anton Chechetka, Carlos Guestrin
Beyond Actions: Discriminative Models for Contextual Group Activities Tian Lan, Yang Wang, Weilong Yang, Greg Mori
Decoding Ipsilateral Finger Movements from ECoG Signals in Humans Yuzong Liu, Mohit Sharma, Charles Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Eric Leuthardt, Kilian Q. Weinberger
New Adaptive Algorithms for Online Classification Francesco Orabona, Koby Crammer
Phoneme Recognition with Large Hierarchical Reservoirs Fabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen, Jean-pierre Martens
Learning Multiple Tasks using Manifold Regularization Arvind Agarwal, Samuel Gerber, Hal Daume
Group Sparse Coding with a Laplacian Scale Mixture Prior Pierre Garrigues, Bruno A. Olshausen
Fractionally Predictive Spiking Neurons Jaldert Rombouts, Sander M. Bohte
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Han Liu, Kathryn Roeder, Larry Wasserman
More data means less inference: A pseudo-max approach to structured learning David Sontag, Ofer Meshi, Amir Globerson, Tommi S. Jaakkola
Lifted Inference Seen from the Other Side : The Tractable Features Abhay Jha, Vibhav Gogate, Alexandra Meliou, Dan Suciu
Predictive State Temporal Difference Learning Byron Boots, Geoffrey J. Gordon
Identifying Dendritic Processing Aurel A. Lazar, Yevgeniy Slutskiy
On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient Tang Jie, Pieter Abbeel
Functional Geometry Alignment and Localization of Brain Areas Georg Langs, Yanmei Tie, Laura Rigolo, Alexandra Golby, Polina Golland
Multi-View Active Learning in the Non-Realizable Case Wei Wang, Zhi-Hua Zhou
Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures Kamiya Motwani, Nagesh Adluru, Chris Hinrichs, Andrew Alexander, Vikas Singh
Over-complete representations on recurrent neural networks can support persistent percepts Shaul Druckmann, Dmitri B. Chklovskii
Non-Stochastic Bandit Slate Problems Satyen Kale, Lev Reyzin, Robert E. Schapire
Large Margin Learning of Upstream Scene Understanding Models Jun Zhu, Li-jia Li, Li Fei-fei, Eric P. Xing
Switched Latent Force Models for Movement Segmentation Mauricio Alvarez, Jan R. Peters, Neil D. Lawrence, Bernhard Schölkopf
Adaptive Multi-Task Lasso: with Application to eQTL Detection Seunghak Lee, Jun Zhu, Eric P. Xing
Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations Danial Lashkari, Ramesh Sridharan, Polina Golland
Random Projection Trees Revisited Aman Dhesi, Purushottam Kar
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin, David B. Dunson
Discriminative Clustering by Regularized Information Maximization Andreas Krause, Pietro Perona, Ryan G. Gomes
Learning to localise sounds with spiking neural networks Dan Goodman, Romain Brette
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis Katsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda, Joshua B. Tenenbaum
Exact learning curves for Gaussian process regression on large random graphs Matthew Urry, Peter Sollich
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies Paul Mckeigue, Jon Krohn, Amos J. Storkey, Felix V. Agakov
Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks Atsushi Miyamae, Yuichi Nagata, Isao Ono, Shigenobu Kobayashi
Kernel Descriptors for Visual Recognition Liefeng Bo, Xiaofeng Ren, Dieter Fox
Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning Matthias Broecheler, Lise Getoor
Gaussian Process Preference Elicitation Shengbo Guo, Scott Sanner, Edwin V. Bonilla
A Theory of Multiclass Boosting Indraneel Mukherjee, Robert E. Schapire
Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning Prateek Jain, Sudheendra Vijayanarasimhan, Kristen Grauman
Bootstrapping Apprenticeship Learning Abdeslam Boularias, Brahim Chaib-draa
Co-regularization Based Semi-supervised Domain Adaptation Abhishek Kumar, Avishek Saha, Hal Daume
Structured sparsity-inducing norms through submodular functions Francis R. Bach
Optimal Web-Scale Tiering as a Flow Problem Gilbert Leung, Novi Quadrianto, Kostas Tsioutsiouliklis, Alex J. Smola
Slice sampling covariance hyperparameters of latent Gaussian models Iain Murray, Ryan P. Adams
Efficient Optimization for Discriminative Latent Class Models Armand Joulin, Jean Ponce, Francis R. Bach
Universal Kernels on Non-Standard Input Spaces Andreas Christmann, Ingo Steinwart
Worst-Case Linear Discriminant Analysis Yu Zhang, Dit-Yan Yeung
Learning Multiple Tasks with a Sparse Matrix-Normal Penalty Yi Zhang, Jeff G. Schneider
Network Flow Algorithms for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Francis R. Bach, Guillaume R. Obozinski
Active Learning by Querying Informative and Representative Examples Sheng-jun Huang, Rong Jin, Zhi-Hua Zhou
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets Paolo Viappiani, Craig Boutilier
Semi-Supervised Learning with Adversarially Missing Label Information Umar Syed, Ben Taskar
Gated Softmax Classification Roland Memisevic, Christopher Zach, Marc Pollefeys, Geoffrey E. Hinton
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs Dávid Pál, Barnabás Póczos, Csaba Szepesvári
Causal discovery in multiple models from different experiments Tom Claassen, Tom Heskes
Learning Bounds for Importance Weighting Corinna Cortes, Yishay Mansour, Mehryar Mohri
A Reduction from Apprenticeship Learning to Classification Umar Syed, Robert E. Schapire
Extensions of Generalized Binary Search to Group Identification and Exponential Costs Gowtham Bellala, Suresh Bhavnani, Clayton Scott
Feature Set Embedding for Incomplete Data David Grangier, Iain Melvin
Improving Human Judgments by Decontaminating Sequential Dependencies Michael Mozer, Harold Pashler, Matthew Wilder, Robert Lindsey, Matt Jones, Michael N. Jones
Scrambled Objects for Least-Squares Regression Odalric Maillard, Rémi Munos
Subgraph Detection Using Eigenvector L1 Norms Benjamin Miller, Nadya Bliss, Patrick J. Wolfe
Error Propagation for Approximate Policy and Value Iteration Amir-massoud Farahmand, Csaba Szepesvári, Rémi Munos
PAC-Bayesian Model Selection for Reinforcement Learning Mahdi M. Fard, Joelle Pineau
Learning to combine foveal glimpses with a third-order Boltzmann machine Hugo Larochelle, Geoffrey E. Hinton
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm Nathan Srebro, Ruslan Salakhutdinov
Worst-case bounds on the quality of max-product fixed-points Meritxell Vinyals, Jes\'us Cerquides, Alessandro Farinelli, Juan A. Rodríguez-aguilar
A POMDP Extension with Belief-dependent Rewards Mauricio Araya, Olivier Buffet, Vincent Thomas, Françcois Charpillet
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski, Hartwig Siebner, Lars K. Hansen
An Alternative to Low-level-Sychrony-Based Methods for Speech Detection Javier R. Movellan, Paul L. Ruvolo
A rational decision making framework for inhibitory control Pradeep Shenoy, Angela J. Yu, Rajesh P. Rao
Policy gradients in linearly-solvable MDPs Emanuel Todorov
Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework Hongbo Zhou, Qiang Cheng
Learning concept graphs from text with stick-breaking priors America Chambers, Padhraic Smyth, Mark Steyvers
Fast Large-scale Mixture Modeling with Component-specific Data Partitions Bo Thiesson, Chong Wang
Improvements to the Sequence Memoizer Jan Gasthaus, Yee W. Teh
Simultaneous Object Detection and Ranking with Weak Supervision Matthew Blaschko, Andrea Vedaldi, Andrew Zisserman
Generating more realistic images using gated MRF's Marc'aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton
Efficient Minimization of Decomposable Submodular Functions Peter Stobbe, Andreas Krause
Implicit Differentiation by Perturbation Justin Domke
The Maximal Causes of Natural Scenes are Edge Filters Jose Puertas, Joerg Bornschein, Jörg Lücke
Regularized estimation of image statistics by Score Matching Diederik P. Kingma, Yann L. Cun
Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch Zeeshan Syed, John V. Guttag
Movement extraction by detecting dynamics switches and repetitions Silvia Chiappa, Jan R. Peters
Exact inference and learning for cumulative distribution functions on loopy graphs Nebojsa Jojic, Chris Meek, Jim C. Huang
Spectral Regularization for Support Estimation Ernesto D. Vito, Lorenzo Rosasco, Alessandro Toigo
Online Learning for Latent Dirichlet Allocation Matthew Hoffman, Francis R. Bach, David M. Blei
Random Projections for $k$-means Clustering Christos Boutsidis, Anastasios Zouzias, Petros Drineas
Inference and communication in the game of Password Yang Xu, Charles Kemp
Smoothness, Low Noise and Fast Rates Nathan Srebro, Karthik Sridharan, Ambuj Tewari
Energy Disaggregation via Discriminative Sparse Coding J. Z. Kolter, Siddharth Batra, Andrew Y. Ng
Random Conic Pursuit for Semidefinite Programming Ariel Kleiner, Ali Rahimi, Michael I. Jordan
Deterministic Single-Pass Algorithm for LDA Issei Sato, Kenichi Kurihara, Hiroshi Nakagawa
A Bayesian Framework for Figure-Ground Interpretation Vicky Froyen, Jacob Feldman, Manish Singh
Online Markov Decision Processes under Bandit Feedback Gergely Neu, Andras Antos, András György, Csaba Szepesvári
A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration Yi-da Wu, Shi-jie Lin, Hsin Chen
SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system Sylvain Chevallier, Hél\`ene Paugam-moisy, Michele Sebag
Permutation Complexity Bound on Out-Sample Error Malik Magdon-Ismail
Fast global convergence rates of gradient methods for high-dimensional statistical recovery Alekh Agarwal, Sahand Negahban, Martin J. Wainwright
Attractor Dynamics with Synaptic Depression K. Wong, He Wang, Si Wu, Chi Fung
Layer-wise analysis of deep networks with Gaussian kernels Grégoire Montavon, Klaus-Robert Müller, Mikio L. Braun
Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake Stefan Harmeling, Hirsch Michael, Bernhard Schölkopf
Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models Anand Singh, Renaud Jolivet, Pierre Magistretti, Bruno Weber
Global Analytic Solution for Variational Bayesian Matrix Factorization Shinichi Nakajima, Masashi Sugiyama, Ryota Tomioka
Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez
Linear Complementarity for Regularized Policy Evaluation and Improvement Jeffrey Johns, Christopher Painter-wakefield, Ronald Parr
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks Dirk Husmeier, Frank Dondelinger, Sophie Lebre
Graph-Valued Regression Han Liu, Xi Chen, Larry Wasserman, John D. Lafferty
Probabilistic Multi-Task Feature Selection Yu Zhang, Dit-Yan Yeung, Qian Xu
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks Ali Shojaie, George Michailidis
Bayesian Action-Graph Games Albert X. Jiang, Kevin Leyton-brown
A Family of Penalty Functions for Structured Sparsity Jean Morales, Charles A. Micchelli, Massimiliano Pontil
Spike timing-dependent plasticity as dynamic filter Joscha Schmiedt, Christian Albers, Klaus Pawelzik
The Neural Costs of Optimal Control Samuel Gershman, Robert Wilson
Sample Complexity of Testing the Manifold Hypothesis Hariharan Narayanan, Sanjoy Mitter
A biologically plausible network for the computation of orientation dominance Kritika Muralidharan, Nuno Vasconcelos
A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups Sofia Mosci, Silvia Villa, Alessandro Verri, Lorenzo Rosasco
Heavy-Tailed Process Priors for Selective Shrinkage Fabian L. Wauthier, Michael I. Jordan
A New Probabilistic Model for Rank Aggregation Tao Qin, Xiubo Geng, Tie-yan Liu
Learning Networks of Stochastic Differential Equations José Pereira, Morteza Ibrahimi, Andrea Montanari
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach Ning Chen, Jun Zhu, Eric P. Xing
A Bayesian Approach to Concept Drift Stephen Bach, Mark Maloof
Multivariate Dyadic Regression Trees for Sparse Learning Problems Han Liu, Xi Chen
A novel family of non-parametric cumulative based divergences for point processes Sohan Seth, Park Il, Austin Brockmeier, Mulugeta Semework, John Choi, Joseph Francis, Jose Principe
Sidestepping Intractable Inference with Structured Ensemble Cascades David Weiss, Benjamin Sapp, Ben Taskar
Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings Ziv Bar-joseph, Hai-son P. Le
t-logistic regression Nan Ding, S.v.n. Vishwanathan
Occlusion Detection and Motion Estimation with Convex Optimization Alper Ayvaci, Michalis Raptis, Stefano Soatto
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach Alessandro Bergamo, Lorenzo Torresani
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression Ling Huang, Jinzhu Jia, Bin Yu, Byung-gon Chun, Petros Maniatis, Mayur Naik
Humans Learn Using Manifolds, Reluctantly Tim Rogers, Chuck Kalish, Joseph Harrison, Xiaojin Zhu, Bryan R. Gibson
Sphere Embedding: An Application to Part-of-Speech Induction Yariv Maron, Michael Lamar, Elie Bienenstock
Tight Sample Complexity of Large-Margin Learning Sivan Sabato, Nathan Srebro, Naftali Tishby
Minimum Average Cost Clustering Kiyohito Nagano, Yoshinobu Kawahara, Satoru Iwata
Online Classification with Specificity Constraints Andrey Bernstein, Shie Mannor, Nahum Shimkin
Construction of Dependent Dirichlet Processes based on Poisson Processes Dahua Lin, Eric Grimson, John W. Fisher
Practical Large-Scale Optimization for Max-norm Regularization Jason Lee, Ben Recht, Nathan Srebro, Joel Tropp, Ruslan Salakhutdinov
Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication Guy Isely, Christopher Hillar, Fritz Sommer
Learning Convolutional Feature Hierarchies for Visual Recognition Koray Kavukcuoglu, Pierre Sermanet, Y-lan Boureau, Karol Gregor, Michael Mathieu, Yann L. Cun
Multiple Kernel Learning and the SMO Algorithm Zhaonan Sun, Nawanol Ampornpunt, Manik Varma, S.v.n. Vishwanathan
Segmentation as Maximum-Weight Independent Set William Brendel, Sinisa Todorovic
Static Analysis of Binary Executables Using Structural SVMs Nikos Karampatziakis
Factorized Latent Spaces with Structured Sparsity Yangqing Jia, Mathieu Salzmann, Trevor Darrell
A unified model of short-range and long-range motion perception Shuang Wu, Xuming He, Hongjing Lu, Alan L. Yuille
Structural epitome: a way to summarize one’s visual experience Nebojsa Jojic, Alessandro Perina, Vittorio Murino
Tree-Structured Stick Breaking for Hierarchical Data Zoubin Ghahramani, Michael I. Jordan, Ryan P. Adams
LSTD with Random Projections Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric Maillard, Rémi Munos
Feature Construction for Inverse Reinforcement Learning Sergey Levine, Zoran Popovic, Vladlen Koltun
An analysis on negative curvature induced by singularity in multi-layer neural-network learning Eiji Mizutani, Stuart Dreyfus
Joint Cascade Optimization Using A Product Of Boosted Classifiers Leonidas Lefakis, Francois Fleuret
Parallelized Stochastic Gradient Descent Martin Zinkevich, Markus Weimer, Lihong Li, Alex J. Smola
Shadow Dirichlet for Restricted Probability Modeling Bela Frigyik, Maya Gupta, Yihua Chen
MAP estimation in Binary MRFs via Bipartite Multi-cuts Sashank J. Reddi, Sunita Sarawagi, Sundar Vishwanathan
Approximate Inference by Compilation to Arithmetic Circuits Daniel Lowd, Pedro Domingos
Random Walk Approach to Regret Minimization Hariharan Narayanan, Alexander Rakhlin
Unsupervised Kernel Dimension Reduction Meihong Wang, Fei Sha, Michael I. Jordan
Multitask Learning without Label Correspondences Novi Quadrianto, James Petterson, Tibério S. Caetano, Alex J. Smola, S.v.n. Vishwanathan
CUR from a Sparse Optimization Viewpoint Jacob Bien, Ya Xu, Michael W. Mahoney
Robust Clustering as Ensembles of Affinity Relations Hairong Liu, Longin J. Latecki, Shuicheng Yan
Optimal learning rates for Kernel Conjugate Gradient regression Gilles Blanchard, Nicole Krämer
Rates of convergence for the cluster tree Kamalika Chaudhuri, Sanjoy Dasgupta
Throttling Poisson Processes Uwe Dick, Peter Haider, Thomas Vanck, Michael Brückner, Tobias Scheffer
An Approximate Inference Approach to Temporal Optimization in Optimal Control Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar
Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine George Dahl, Marc'aurelio Ranzato, Abdel-rahman Mohamed, Geoffrey E. Hinton
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives Taehwan Kim, Gregory Shakhnarovich, Raquel Urtasun
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference Vikas Sindhwani, Aurelie C. Lozano
Reverse Multi-Label Learning James Petterson, Tibério S. Caetano
Efficient Relational Learning with Hidden Variable Detection Ni Lao, Jun Zhu, Liu Liu, Yandong Liu, William W. Cohen
Learning from Logged Implicit Exploration Data Alex Strehl, John Langford, Lihong Li, Sham M. Kakade
Parametric Bandits: The Generalized Linear Case Sarah Filippi, Olivier Cappe, Aurélien Garivier, Csaba Szepesvári
Basis Construction from Power Series Expansions of Value Functions Sridhar Mahadevan, Bo Liu
A Novel Kernel for Learning a Neuron Model from Spike Train Data Nicholas Fisher, Arunava Banerjee
Nonparametric Bayesian Policy Priors for Reinforcement Learning Finale Doshi-velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum
On the Theory of Learnining with Privileged Information Dmitry Pechyony, Vladimir Vapnik
Accounting for network effects in neuronal responses using L1 regularized point process models Ryan Kelly, Matthew Smith, Robert Kass, Tai S. Lee
Probabilistic latent variable models for distinguishing between cause and effect Oliver Stegle, Dominik Janzing, Kun Zhang, Joris M. Mooij, Bernhard Schölkopf
Two-Layer Generalization Analysis for Ranking Using Rademacher Average Wei Chen, Tie-yan Liu, Zhi-ming Ma
Learning from Candidate Labeling Sets Jie Luo, Francesco Orabona
Direct Loss Minimization for Structured Prediction Tamir Hazan, Joseph Keshet, David A. McAllester
Variational Inference over Combinatorial Spaces Alexandre Bouchard-côté, Michael I. Jordan
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner, Lawrence K. Saul
Avoiding False Positive in Multi-Instance Learning Yanjun Han, Qing Tao, Jue Wang
Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles Kaiming Li, Lei Guo, Carlos Faraco, Dajiang Zhu, Fan Deng, Tuo Zhang, Xi Jiang, Degang Zhang, Hanbo Chen, Xintao Hu, Steve Miller, Tianming Liu
On the Convexity of Latent Social Network Inference Seth Myers, Jure Leskovec
Global seismic monitoring as probabilistic inference Nimar Arora, Stuart Russell, Paul Kidwell, Erik B. Sudderth
Gaussian sampling by local perturbations George Papandreou, Alan L. Yuille
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model Peggy Series, David P. Reichert, Amos J. Storkey
Moreau-Yosida Regularization for Grouped Tree Structure Learning Jun Liu, Jieping Ye
Pose-Sensitive Embedding by Nonlinear NCA Regression Graham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler
Synergies in learning words and their referents Mark Johnson, Katherine Demuth, Bevan Jones, Michael J. Black
Approximate inference in continuous time Gaussian-Jump processes Manfred Opper, Andreas Ruttor, Guido Sanguinetti
Empirical Bernstein Inequalities for U-Statistics Thomas Peel, Sandrine Anthoine, Liva Ralaivola
Active Estimation of F-Measures Christoph Sawade, Niels Landwehr, Tobias Scheffer
Inductive Regularized Learning of Kernel Functions Prateek Jain, Brian Kulis, Inderjit S. Dhillon
Active Learning Applied to Patient-Adaptive Heartbeat Classification Jenna Wiens, John V. Guttag
Large-Scale Matrix Factorization with Missing Data under Additional Constraints Kaushik Mitra, Sameer Sheorey, Rama Chellappa
Probabilistic Deterministic Infinite Automata David Pfau, Nicholas Bartlett, Frank Wood
Brain covariance selection: better individual functional connectivity models using population prior Gael Varoquaux, Alexandre Gramfort, Jean-baptiste Poline, Bertrand Thirion
Word Features for Latent Dirichlet Allocation James Petterson, Wray Buntine, Shravan M. Narayanamurthy, Tibério S. Caetano, Alex J. Smola
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction Tamir Hazan, Raquel Urtasun
Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions Achintya Kundu, Vikram Tankasali, Chiranjib Bhattacharyya, Aharon Ben-tal
Online Learning: Random Averages, Combinatorial Parameters, and Learnability Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
Variable margin losses for classifier design Hamed Masnadi-shirazi, Nuno Vasconcelos
Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable Lauren Hannah, Warren Powell, David M. Blei
Mixture of time-warped trajectory models for movement decoding Elaine Corbett, Eric Perreault, Konrad Koerding
A Discriminative Latent Model of Image Region and Object Tag Correspondence Yang Wang, Greg Mori
Lower Bounds on Rate of Convergence of Cutting Plane Methods Xinhua Zhang, Ankan Saha, S.v.n. Vishwanathan
Self-Paced Learning for Latent Variable Models M. P. Kumar, Benjamin Packer, Daphne Koller
Learning Efficient Markov Networks Vibhav Gogate, William Webb, Pedro Domingos
Multi-Stage Dantzig Selector Ji Liu, Peter Wonka, Jieping Ye
Batch Bayesian Optimization via Simulation Matching Javad Azimi, Alan Fern, Xiaoli Z. Fern
Inference with Multivariate Heavy-Tails in Linear Models Danny Bickson, Carlos Guestrin
Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models Congcong Li, Adarsh Kowdle, Ashutosh Saxena, Tsuhan Chen
Learning the context of a category Dan Navarro
Learning via Gaussian Herding Koby Crammer, Daniel D. Lee
Monte-Carlo Planning in Large POMDPs David Silver, Joel Veness
Spatial and anatomical regularization of SVM for brain image analysis Remi Cuingnet, Marie Chupin, Habib Benali, Olivier Colliot
Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform Siwei Lyu
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models Felipe Gerhard, Wulfram Gerstner
Active Instance Sampling via Matrix Partition Yuhong Guo
Functional form of motion priors in human motion perception Hongjing Lu, Tungyou Lin, Alan Lee, Luminita Vese, Alan L. Yuille
The LASSO risk: asymptotic results and real world examples Mohsen Bayati, José Pereira, Andrea Montanari
Layered image motion with explicit occlusions, temporal consistency, and depth ordering Deqing Sun, Erik B. Sudderth, Michael J. Black
Towards Property-Based Classification of Clustering Paradigms Margareta Ackerman, Shai Ben-David, David Loker
Implicit encoding of prior probabilities in optimal neural populations Deep Ganguli, Eero P. Simoncelli
Distributed Dual Averaging In Networks Alekh Agarwal, Martin J. Wainwright, John C. Duchi
Probabilistic Inference and Differential Privacy Oliver Williams, Frank Mcsherry
Copula Processes Andrew G Wilson, Zoubin Ghahramani
Learning invariant features using the Transformed Indian Buffet Process Joseph L. Austerweil, Thomas L. Griffiths
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA Matthias Hein, Thomas Bühler
Fast detection of multiple change-points shared by many signals using group LARS Jean-philippe Vert, Kevin Bleakley
Learning To Count Objects in Images Victor Lempitsky, Andrew Zisserman
Robust PCA via Outlier Pursuit Huan Xu, Constantine Caramanis, Sujay Sanghavi
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition Serhat Bucak, Rong Jin, Anil K. Jain
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors Alessandro Chiuso, Gianluigi Pillonetto

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