Advances in Neural Information Processing Systems 20

NIPS 2007

Edited by J. Platt and D. Koller and Y. Singer and S. Roweis

ISBN: 9781605603520

217 papers

An Analysis of Convex Relaxations for MAP Estimation Pawan Mudigonda, Vladimir Kolmogorov, Philip Torr
Random Features for Large-Scale Kernel Machines Ali Rahimi, Benjamin Recht
Compressed Regression Shuheng Zhou, Larry Wasserman, John D. Lafferty
Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains Andrea Lecchini-visintini, John Lygeros, Jan Maciejowski
Predictive Matrix-Variate t Models Shenghuo Zhu, Kai Yu, Yihong Gong
Loop Series and Bethe Variational Bounds in Attractive Graphical Models Alan S. Willsky, Erik B. Sudderth, Martin J. Wainwright
Stable Dual Dynamic Programming Tao Wang, Michael Bowling, Dale Schuurmans, Daniel J. Lizotte
FilterBoost: Regression and Classification on Large Datasets Joseph K. Bradley, Robert E. Schapire
Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data Sabri Boutemedjet, Djemel Ziou, Nizar Bouguila
Efficient Principled Learning of Thin Junction Trees Anton Chechetka, Carlos Guestrin
Regret Minimization in Games with Incomplete Information Martin Zinkevich, Michael Johanson, Michael Bowling, Carmelo Piccione
A Bayesian Model of Conditioned Perception Alan Stocker, Eero P. Simoncelli
Scan Strategies for Meteorological Radars Victoria Manfredi, Jim Kurose
The Tradeoffs of Large Scale Learning Léon Bottou, Olivier Bousquet
Inferring Elapsed Time from Stochastic Neural Processes Misha Ahrens, Maneesh Sahani
A learning framework for nearest neighbor search Lawrence Cayton, Sanjoy Dasgupta
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
Ensemble Clustering using Semidefinite Programming Vikas Singh, Lopamudra Mukherjee, Jiming Peng, Jinhui Xu
Theoretical Analysis of Heuristic Search Methods for Online POMDPs Stephane Ross, Joelle Pineau, Brahim Chaib-draa
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems Byron Boots, Geoffrey J. Gordon, Sajid M. Siddiqi
An online Hebbian learning rule that performs Independent Component Analysis Claudia Clopath, André Longtin, Wulfram Gerstner
Modeling Natural Sounds with Modulation Cascade Processes Richard Turner, Maneesh Sahani
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition Maryam Mahdaviani, Tanzeem Choudhury
How SVMs can estimate quantiles and the median Andreas Christmann, Ingo Steinwart
Random Projections for Manifold Learning Chinmay Hegde, Michael Wakin, Richard Baraniuk
Hippocampal Contributions to Control: The Third Way Máté Lengyel, Peter Dayan
Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing Yuanhao Chen, Long Zhu, Chenxi Lin, Hongjiang Zhang, Alan L. Yuille
Convex Learning with Invariances Choon H. Teo, Amir Globerson, Sam T. Roweis, Alex J. Smola
The Noisy-Logical Distribution and its Application to Causal Inference Alan L. Yuille, Hongjing Lu
DIFFRAC: a discriminative and flexible framework for clustering Francis R. Bach, Zaïd Harchaoui
Adaptive Online Gradient Descent Peter L. Bartlett, Elad Hazan, Alexander Rakhlin
Bundle Methods for Machine Learning Quoc V. Le, Alex J. Smola, S.v.n. Vishwanathan
Catching Up Faster in Bayesian Model Selection and Model Averaging Tim V. Erven, Steven D. Rooij, Peter Grünwald
Nearest-Neighbor-Based Active Learning for Rare Category Detection Jingrui He, Jaime G. Carbonell
Receptive Fields without Spike-Triggering Guenther Zeck, Matthias Bethge, Jakob H. Macke
Robust Regression with Twinned Gaussian Processes Andrew Naish-guzman, Sean Holden
New Outer Bounds on the Marginal Polytope David Sontag, Tommi S. Jaakkola
Neural characterization in partially observed populations of spiking neurons Jonathan W. Pillow, Peter E. Latham
Bayesian Agglomerative Clustering with Coalescents Yee W. Teh, Hal Daume III, Daniel M. Roy
Distributed Inference for Latent Dirichlet Allocation David Newman, Padhraic Smyth, Max Welling, Arthur U. Asuncion
Better than least squares: comparison of objective functions for estimating linear-nonlinear models Tatyana Sharpee
Structured Learning with Approximate Inference Alex Kulesza, Fernando Pereira
On Ranking in Survival Analysis: Bounds on the Concordance Index Harald Steck, Balaji Krishnapuram, Cary Dehing-oberije, Philippe Lambin, Vikas C. Raykar
Competition Adds Complexity Judy Goldsmith, Martin Mundhenk
Classification via Minimum Incremental Coding Length (MICL) John Wright, Yangyu Tao, Zhouchen Lin, Yi Ma, Heung-yeung Shum
Kernel Measures of Conditional Dependence Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf
Bayesian Policy Learning with Trans-Dimensional MCMC Matthew Hoffman, Arnaud Doucet, Nando D. Freitas, Ajay Jasra
Temporal Difference Updating without a Learning Rate Marcus Hutter, Shane Legg
Bayes-Adaptive POMDPs Stephane Ross, Brahim Chaib-draa, Joelle Pineau
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach José M. Hernández-lobato, Tjeerd Dijkstra, Tom Heskes
Convex Clustering with Exemplar-Based Models Danial Lashkari, Polina Golland
Learning Bounds for Domain Adaptation John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman
SpAM: Sparse Additive Models Han Liu, Larry Wasserman, John D. Lafferty, Pradeep K. Ravikumar
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior Sebastian Gerwinn, Matthias Bethge, Jakob H. Macke, Matthias Seeger
Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks Alex Graves, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber, Santiago Fernández
The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information John Langford, Tong Zhang
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes Geoffrey E. Hinton, Ruslan Salakhutdinov
Kernels on Attributed Pointsets with Applications Mehul Parsana, Sourangshu Bhattacharya, Chiru Bhattacharya, K. Ramakrishnan
Testing for Homogeneity with Kernel Fisher Discriminant Analysis Moulines Eric, Francis R. Bach, Zaïd Harchaoui
Sparse deep belief net model for visual area V2 Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
Second Order Bilinear Discriminant Analysis for single trial EEG analysis Christoforos Christoforou, Paul Sajda, Lucas C. Parra
Convex Relaxations of Latent Variable Training Yuhong Guo, Dale Schuurmans
A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses Massimiliano Giulioni, Mario Pannunzi, Davide Badoni, Vittorio Dante, Paolo D. Giudice
The discriminant center-surround hypothesis for bottom-up saliency Dashan Gao, Vijay Mahadevan, Nuno Vasconcelos
Statistical Analysis of Semi-Supervised Regression Larry Wasserman, John D. Lafferty
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion J. Z. Kolter, Pieter Abbeel, Andrew Y. Ng
Colored Maximum Variance Unfolding Le Song, Arthur Gretton, Karsten Borgwardt, Alex J. Smola
Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson
Ultrafast Monte Carlo for Statistical Summations Charles L. Isbell, Michael P. Holmes, Alexander G. Gray
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani
People Tracking with the Laplacian Eigenmaps Latent Variable Model Zhengdong Lu, Cristian Sminchisescu, Miguel Á. Carreira-Perpiñán
The Distribution Family of Similarity Distances Gertjan Burghouts, Arnold Smeulders, Jan-mark Geusebroek
Congruence between model and human attention reveals unique signatures of critical visual events Robert Peters, Laurent Itti
Multi-task Gaussian Process Prediction Edwin V. Bonilla, Kian M. Chai, Christopher Williams
Multi-Task Learning via Conic Programming Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai
Incremental Natural Actor-Critic Algorithms Shalabh Bhatnagar, Mohammad Ghavamzadeh, Mark Lee, Richard S. Sutton
Collective Inference on Markov Models for Modeling Bird Migration M.a. S. Elmohamed, Dexter Kozen, Daniel R. Sheldon
EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection Pierre Ferrez, José Millán
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike Hohlefeld, Klaus-Robert Müller, Vadim V. Nikulin
The Infinite Gamma-Poisson Feature Model Michalis K. Titsias
A Unified Near-Optimal Estimator For Dimension Reduction in $l_\alpha$ ($0<\alpha\leq 2$) Using Stable Random Projections Ping Li, Trevor J. Hastie
Continuous Time Particle Filtering for fMRI Lawrence Murray, Amos J. Storkey
Computing Robust Counter-Strategies Michael Johanson, Martin Zinkevich, Michael Bowling
Random Sampling of States in Dynamic Programming Chris Atkeson, Benjamin Stephens
Predicting human gaze using low-level saliency combined with face detection Moran Cerf, Jonathan Harel, Wolfgang Einhaeuser, Christof Koch
Local Algorithms for Approximate Inference in Minor-Excluded Graphs Kyomin Jung, Devavrat Shah
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization Xuanlong Nguyen, Martin J. Wainwright, Michael I. Jordan
Learning with Tree-Averaged Densities and Distributions Sergey Kirshner
Variational inference for Markov jump processes Manfred Opper, Guido Sanguinetti
Expectation Maximization and Posterior Constraints Kuzman Ganchev, Ben Taskar, João Gama
Anytime Induction of Cost-sensitive Trees Saher Esmeir, Shaul Markovitch
Optimal ROC Curve for a Combination of Classifiers Marco Barreno, Alvaro Cardenas, J. D. Tygar
Modeling homophily and stochastic equivalence in symmetric relational data Peter Hoff
On Sparsity and Overcompleteness in Image Models Pietro Berkes, Richard Turner, Maneesh Sahani
A Probabilistic Approach to Language Change Alexandre Bouchard-côté, Percy Liang, Dan Klein, Thomas L. Griffiths
Learning the 2-D Topology of Images Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl
A Bayesian LDA-based model for semi-supervised part-of-speech tagging Kristina Toutanova, Mark Johnson
Cluster Stability for Finite Samples Ohad Shamir, Naftali Tishby
Variational Inference for Diffusion Processes Cédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford, John S. Shawe-taylor
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes Nicolas Chapados, Yoshua Bengio
Sparse Overcomplete Latent Variable Decomposition of Counts Data Madhusudana Shashanka, Bhiksha Raj, Paris Smaragdis
Modelling motion primitives and their timing in biologically executed movements Ben Williams, Marc Toussaint, Amos J. Storkey
Subspace-Based Face Recognition in Analog VLSI Gonzalo Carvajal, Waldo Valenzuela, Miguel Figueroa
Efficient multiple hyperparameter learning for log-linear models Chuan-sheng Foo, Chuong B. Do, Andrew Y. Ng
Discovering Weakly-Interacting Factors in a Complex Stochastic Process Charlie Frogner, Avi Pfeffer
Stability Bounds for Non-i.i.d. Processes Mehryar Mohri, Afshin Rostamizadeh
Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks Ben Carterette, Rosie Jones
Efficient Bayesian Inference for Dynamically Changing Graphs Ozgur Sumer, Umut Acar, Alexander T. Ihler, Ramgopal R. Mettu
Markov Chain Monte Carlo with People Adam Sanborn, Thomas L. Griffiths
Estimating disparity with confidence from energy neurons Eric K. Tsang, Bertram E. Shi
Locality and low-dimensions in the prediction of natural experience from fMRI Francois Meyer, Greg Stephens
Configuration Estimates Improve Pedestrian Finding Duan Tran, David A. Forsyth
A General Boosting Method and its Application to Learning Ranking Functions for Web Search Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun
Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations Amir Globerson, Tommi S. Jaakkola
GRIFT: A graphical model for inferring visual classification features from human data Michael Ross, Andrew Cohen
An in-silico Neural Model of Dynamic Routing through Neuronal Coherence Devarajan Sridharan, Brian Percival, John Arthur, Kwabena A. Boahen
A general agnostic active learning algorithm Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni
Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass
Hidden Common Cause Relations in Relational Learning Ricardo Silva, Wei Chu, Zoubin Ghahramani
Modeling image patches with a directed hierarchy of Markov random fields Simon Osindero, Geoffrey E. Hinton
The Generalized FITC Approximation Andrew Naish-guzman, Sean Holden
Cooled and Relaxed Survey Propagation for MRFs Hai L. Chieu, Wee S. Lee, Yee W. Teh
A Spectral Regularization Framework for Multi-Task Structure Learning Andreas Argyriou, Massimiliano Pontil, Yiming Ying, Charles A. Micchelli
CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation Luis E. Ortiz
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity Dejan Pecevski, Wolfgang Maass, Robert A. Legenstein
A New View of Automatic Relevance Determination David P. Wipf, Srikantan S. Nagarajan
Sequential Hypothesis Testing under Stochastic Deadlines Peter Frazier, Angela J. Yu
Discriminative Log-Linear Grammars with Latent Variables Slav Petrov, Dan Klein
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation Bing Zhao, Eric P. Xing
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs Ambuj Tewari, Peter L. Bartlett
TrueSkill Through Time: Revisiting the History of Chess Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel
Topmoumoute Online Natural Gradient Algorithm Nicolas L. Roux, Pierre-antoine Manzagol, Yoshua Bengio
Learning the structure of manifolds using random projections Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma
Learning Monotonic Transformations for Classification Andrew Howard, Tony Jebara
Combined discriminative and generative articulated pose and non-rigid shape estimation Leonid Sigal, Alexandru Balan, Michael J. Black
Multiple-Instance Active Learning Burr Settles, Mark Craven, Soumya Ray
Semi-Supervised Multitask Learning Qiuhua Liu, Xuejun Liao, Lawrence Carin
Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons Emre Neftci, Elisabetta Chicca, Giacomo Indiveri, Jean-jeacques Slotine, Rodney J. Douglas
Mining Internet-Scale Software Repositories Erik Linstead, Paul Rigor, Sushil Bajracharya, Cristina Lopes, Pierre F. Baldi
Optimal models of sound localization by barn owls Brian J. Fischer
Discriminative K-means for Clustering Jieping Ye, Zheng Zhao, Mingrui Wu
Heterogeneous Component Analysis Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii
An Analysis of Inference with the Universum Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz, Bernhard Schölkopf
Exponential Family Predictive Representations of State David Wingate, Satinder S. Baveja
One-Pass Boosting Zafer Barutcuoglu, Phil Long, Rocco Servedio
The Value of Labeled and Unlabeled Examples when the Model is Imperfect Kaushik Sinha, Mikhail Belkin
On higher-order perceptron algorithms Claudio Gentile, Fabio Vitale, Cristian Brotto
Fast Variational Inference for Large-scale Internet Diagnosis Emre Kiciman, David Maltz, John C. Platt
Learning and using relational theories Charles Kemp, Noah Goodman, Joshua B. Tenenbaum
The Infinite Markov Model Daichi Mochihashi, Eiichiro Sumita
Retrieved context and the discovery of semantic structure Vinayak Rao, Marc Howard
Active Preference Learning with Discrete Choice Data Brochu Eric, Nando D. Freitas, Abhijeet Ghosh
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms Dominik Endres, Mike Oram, Johannes Schindelin, Peter Foldiak
Online Linear Regression and Its Application to Model-Based Reinforcement Learning Alexander L. Strehl, Michael L. Littman
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations M. M. Mahmud, Sylvian Ray
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting Ping Li, Qiang Wu, Christopher J. Burges
A Randomized Algorithm for Large Scale Support Vector Learning Krishnan Kumar, Chiru Bhattacharya, Ramesh Hariharan
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V. Buenau, Motoaki Kawanabe
The Price of Bandit Information for Online Optimization Varsha Dani, Sham M. Kakade, Thomas P. Hayes
Iterative Non-linear Dimensionality Reduction with Manifold Sculpting Michael Gashler, Dan Ventura, Tony Martinez
Support Vector Machine Classification with Indefinite Kernels Ronny Luss, Alexandre D'aspremont
Learning with Transformation Invariant Kernels Christian Walder, Olivier Chapelle
A probabilistic model for generating realistic lip movements from speech Gwenn Englebienne, Tim Cootes, Magnus Rattray
Automatic Generation of Social Tags for Music Recommendation Douglas Eck, Paul Lamere, Thierry Bertin-mahieux, Stephen Green
Learning to classify complex patterns using a VLSI network of spiking neurons Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
Efficient Convex Relaxation for Transductive Support Vector Machine Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu
Message Passing for Max-weight Independent Set Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
Boosting the Area under the ROC Curve Phil Long, Rocco Servedio
Sparse Feature Learning for Deep Belief Networks Marc'aurelio Ranzato, Y-lan Boureau, Yann L. Cun
Receding Horizon Differential Dynamic Programming Yuval Tassa, Tom Erez, William D. Smart
A Risk Minimization Principle for a Class of Parzen Estimators Kristiaan Pelckmans, Johan Suykens, Bart D. Moor
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning Gerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey Kephart, David Levine, Freeman Rawson, Charles Lefurgy
A Game-Theoretic Approach to Apprenticeship Learning Umar Syed, Robert E. Schapire
Scene Segmentation with CRFs Learned from Partially Labeled Images Bill Triggs, Jakob J. Verbeek
Measuring Neural Synchrony by Message Passing Justin Dauwels, François Vialatte, Tomasz Rutkowski, Andrzej S. Cichocki
Discriminative Batch Mode Active Learning Yuhong Guo, Dale Schuurmans
Comparing Bayesian models for multisensory cue combination without mandatory integration Ulrik Beierholm, Ladan Shams, Wei J. Ma, Konrad Koerding
What makes some POMDP problems easy to approximate? Wee S. Lee, Nan Rong, David Hsu
Boosting Algorithms for Maximizing the Soft Margin Gunnar Rätsch, Manfred K. Warmuth, Karen A. Glocer
Gaussian Process Models for Link Analysis and Transfer Learning Kai Yu, Wei Chu
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images Matthias Bethge, Philipp Berens
Privacy-Preserving Belief Propagation and Sampling Michael Kearns, Jinsong Tan, Jennifer Wortman
Bayesian Co-Training Shipeng Yu, Balaji Krishnapuram, Harald Steck, R. B. Rao, Rómer Rosales
Supervised Topic Models Jon D. Mcauliffe, David M. Blei
A Kernel Statistical Test of Independence Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf, Alex J. Smola
Discriminative Keyword Selection Using Support Vector Machines Fred Richardson, William M. Campbell
Probabilistic Matrix Factorization Andriy Mnih, Ruslan Salakhutdinov
Density Estimation under Independent Similarly Distributed Sampling Assumptions Tony Jebara, Yingbo Song, Kapil Thadani
Efficient Inference for Distributions on Permutations Jonathan Huang, Carlos Guestrin, Leonidas Guibas
Fitted Q-iteration in continuous action-space MDPs András Antos, Csaba Szepesvári, Rémi Munos
Blind channel identification for speech dereverberation using l1-norm sparse learning Yuanqing Lin, Jingdong Chen, Youngmoo Kim, Daniel D. Lee
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression Sennay Ghebreab, Arnold Smeulders, Pieter Adriaans
Agreement-Based Learning Percy Liang, Dan Klein, Michael I. Jordan
Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination Yiu M. Lam, Bertram E. Shi
A Bayesian Framework for Cross-Situational Word-Learning Noah Goodman, Joshua B. Tenenbaum, Michael J. Black
Parallelizing Support Vector Machines on Distributed Computers Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, Hang Cui, Edward Y. Chang
Object Recognition by Scene Alignment Bryan Russell, Antonio Torralba, Ce Liu, Rob Fergus, William T. Freeman
A neural network implementing optimal state estimation based on dynamic spike train decoding Omer Bobrowski, Ron Meir, Shy Shoham, Yonina Eldar
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria Elad Hazan, Satyen Kale
Catching Change-points with Lasso Céline Levy-leduc, Zaïd Harchaoui
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta Ben Blum, David Baker, Michael I. Jordan, Philip Bradley, Rhiju Das, David E Kim
Selecting Observations against Adversarial Objectives Andreas Krause, Brendan Mcmahan, Carlos Guestrin, Anupam Gupta
Spatial Latent Dirichlet Allocation Xiaogang Wang, Eric Grimson
Learning Visual Attributes Vittorio Ferrari, Andrew Zisserman
Collapsed Variational Inference for HDP Yee W. Teh, Kenichi Kurihara, Max Welling
Progressive mixture rules are deviation suboptimal Jean-yves Audibert
Experience-Guided Search: A Theory of Attentional Control David Baldwin, Michael Mozer
Hierarchical Penalization Marie Szafranski, Yves Grandvalet, Pierre Morizet-mahoudeaux
Linear programming analysis of loopy belief propagation for weighted matching Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky
Learning Horizontal Connections in a Sparse Coding Model of Natural Images Pierre Garrigues, Bruno A. Olshausen
COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alex J. Smola
Infinite State Bayes-Nets for Structured Domains Max Welling, Ian Porteous, Evgeniy Bart
Regularized Boost for Semi-Supervised Learning Ke Chen, Shihai Wang
Consistent Minimization of Clustering Objective Functions Ulrike V. Luxburg, Stefanie Jegelka, Michael Kaufmann, Sébastien Bubeck
The rat as particle filter Aaron C. Courville, Nathaniel D. Daw
Non-parametric Modeling of Partially Ranked Data Guy Lebanon, Yi Mao
Multiple-Instance Pruning For Learning Efficient Cascade Detectors Cha Zhang, Paul A. Viola

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