NeurIPS 2007
217 papers
A General Agnostic Active Learning Algorithm
Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni A Kernel Statistical Test of Independence
Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf, Alex J. Smola A Probabilistic Approach to Language Change
Alexandre Bouchard-côté, Percy Liang, Dan Klein, Thomas L. Griffiths A Spectral Regularization Framework for Multi-Task Structure Learning
Andreas Argyriou, Massimiliano Pontil, Yiming Ying, Charles A. Micchelli Adaptive Online Gradient Descent
Peter L. Bartlett, Elad Hazan, Alexander Rakhlin Agreement-Based Learning
Percy Liang, Dan Klein, Michael I. Jordan An Analysis of Inference with the Universum
Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz, Bernhard Schölkopf Automatic Generation of Social Tags for Music Recommendation
Douglas Eck, Paul Lamere, Thierry Bertin-mahieux, Stephen Green Bayes-Adaptive POMDPs
Stephane Ross, Brahim Chaib-draa, Joelle Pineau Bayesian Co-Training
Shipeng Yu, Balaji Krishnapuram, Harald Steck, R. B. Rao, Rómer Rosales Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Sebastian Gerwinn, Matthias Bethge, Jakob H. Macke, Matthias Seeger Bayesian Policy Learning with Trans-Dimensional MCMC
Matthew Hoffman, Arnaud Doucet, Nando D. Freitas, Ajay Jasra Boosting Algorithms for Maximizing the Soft Margin
Gunnar Rätsch, Manfred K. Warmuth, Karen A. Glocer Bundle Methods for Machine Learning
Quoc V. Le, Alex J. Smola, S.v.n. Vishwanathan Catching Change-Points with Lasso
Céline Levy-leduc, Zaïd Harchaoui Classification via Minimum Incremental Coding Length (MICL)
John Wright, Yangyu Tao, Zhouchen Lin, Yi Ma, Heung-yeung Shum Collapsed Variational Inference for HDP
Yee W. Teh, Kenichi Kurihara, Max Welling Colored Maximum Variance Unfolding
Le Song, Arthur Gretton, Karsten Borgwardt, Alex J. Smola Competition Adds Complexity
Judy Goldsmith, Martin Mundhenk Compressed Regression
Shuheng Zhou, Larry Wasserman, John D. Lafferty Computing Robust Counter-Strategies
Michael Johanson, Martin Zinkevich, Michael Bowling Consistent Minimization of Clustering Objective Functions
Ulrike V. Luxburg, Stefanie Jegelka, Michael Kaufmann, Sébastien Bubeck Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons
Emre Neftci, Elisabetta Chicca, Giacomo Indiveri, Jean-jeacques Slotine, Rodney J. Douglas Convex Learning with Invariances
Choon H. Teo, Amir Globerson, Sam T. Roweis, Alex J. Smola Distributed Inference for Latent Dirichlet Allocation
David Newman, Padhraic Smyth, Max Welling, Arthur U. Asuncion Efficient Bayesian Inference for Dynamically Changing Graphs
Ozgur Sumer, Umut Acar, Alexander T. Ihler, Ramgopal R. Mettu Ensemble Clustering Using Semidefinite Programming
Vikas Singh, Lopamudra Mukherjee, Jiming Peng, Jinhui Xu Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Ben Blum, David Baker, Michael I. Jordan, Philip Bradley, Rhiju Das, David E Kim Heterogeneous Component Analysis
Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii Hierarchical Penalization
Marie Szafranski, Yves Grandvalet, Pierre Morizet-mahoudeaux Incremental Natural Actor-Critic Algorithms
Shalabh Bhatnagar, Mohammad Ghavamzadeh, Mark Lee, Richard S. Sutton Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike Hohlefeld, Klaus-Robert Müller, Vadim V. Nikulin Kernel Measures of Conditional Dependence
Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf Kernels on Attributed Pointsets with Applications
Mehul Parsana, Sourangshu Bhattacharya, Chiru Bhattacharya, K. Ramakrishnan Learning and Using Relational Theories
Charles Kemp, Noah Goodman, Joshua B. Tenenbaum Learning Bounds for Domain Adaptation
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Learning the 2-D Topology of Images
Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl Learning Visual Attributes
Vittorio Ferrari, Andrew Zisserman 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 Measuring Neural Synchrony by Message Passing
Justin Dauwels, François Vialatte, Tomasz Rutkowski, Andrzej S. Cichocki Message Passing for Max-Weight Independent Set
Sujay Sanghavi, Devavrat Shah, Alan S. Willsky Mining Internet-Scale Software Repositories
Erik Linstead, Paul Rigor, Sushil Bajracharya, Cristina Lopes, Pierre F. Baldi 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 Multiple-Instance Active Learning
Burr Settles, Mark Craven, Soumya Ray Object Recognition by Scene Alignment
Bryan Russell, Antonio Torralba, Ce Liu, Rob Fergus, William T. Freeman On Higher-Order Perceptron Algorithms
Claudio Gentile, Fabio Vitale, Cristian Brotto On Ranking in Survival Analysis: Bounds on the Concordance Index
Harald Steck, Balaji Krishnapuram, Cary Dehing-oberije, Philippe Lambin, Vikas C. Raykar One-Pass Boosting
Zafer Barutcuoglu, Phil Long, Rocco Servedio Parallelizing Support Vector Machines on Distributed Computers
Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, Hang Cui, Edward Y. Chang Predictive Matrix-Variate T Models
Shenghuo Zhu, Kai Yu, Yihong Gong Probabilistic Matrix Factorization
Andriy Mnih, Ruslan Salakhutdinov Random Projections for Manifold Learning
Chinmay Hegde, Michael Wakin, Richard Baraniuk Receptive Fields Without Spike-Triggering
Guenther Zeck, Matthias Bethge, Jakob H. Macke Regret Minimization in Games with Incomplete Information
Martin Zinkevich, Michael Johanson, Michael Bowling, Carmelo Piccione Selecting Observations Against Adversarial Objectives
Andreas Krause, Brendan Mcmahan, Carlos Guestrin, Anupam Gupta Semi-Supervised Multitask Learning
Qiuhua Liu, Xuejun Liao, Lawrence Carin SpAM: Sparse Additive Models
Han Liu, Larry Wasserman, John D. Lafferty, Pradeep K. Ravikumar Sparse Deep Belief Net Model for Visual Area V2
Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng Sparse Feature Learning for Deep Belief Networks
Marc'aurelio Ranzato, Y-lan Boureau, Yann L. Cun Stable Dual Dynamic Programming
Tao Wang, Michael Bowling, Dale Schuurmans, Daniel J. Lizotte Subspace-Based Face Recognition in Analog VLSI
Gonzalo Carvajal, Waldo Valenzuela, Miguel Figueroa Supervised Topic Models
Jon D. Mcauliffe, David M. Blei The Distribution Family of Similarity Distances
Gertjan Burghouts, Arnold Smeulders, Jan-mark Geusebroek The Infinite Markov Model
Daichi Mochihashi, Eiichiro Sumita The Rat as Particle Filter
Aaron C. Courville, Nathaniel D. Daw Topmoumoute Online Natural Gradient Algorithm
Nicolas L. Roux, Pierre-antoine Manzagol, Yoshua Bengio TrueSkill Through Time: Revisiting the History of Chess
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel Ultrafast Monte Carlo for Statistical Summations
Charles L. Isbell, Michael P. Holmes, Alexander G. Gray Unconstrained On-Line Handwriting Recognition with Recurrent Neural Networks
Alex Graves, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber, Santiago Fernández Variational Inference for Diffusion Processes
Cédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford, John S. Shawe-taylor