NeurIPS 2005
207 papers
A Bayesian Spatial Scan Statistic
Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper A PAC-Bayes Approach to the Set Covering Machine
François Laviolette, Mario Marchand, Mohak Shah Active Learning for Identifying Function Threshold Boundaries
Brent Bryan, Robert C. Nichol, Christopher R Genovese, Jeff Schneider, Christopher J. Miller, Larry Wasserman AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems
R. Serrano-Gotarredona, M. Oster, P. Lichtsteiner, A. Linares-Barranco, R. Paz-Vicente, F. Gomez-Rodriguez, H. Kolle Riis, T. Delbruck, S. C. Liu, S. Zahnd, A. M. Whatley, R. Douglas, P. Hafliger, G. Jimenez-Moreno, A. Civit, T. Serrano-Gotarredona, A. Acosta-Jimenez, B. Linares-Barranco An aVLSI Cricket Ear Model
Andre V. Schaik, Richard Reeve, Craig Jin, Tara Hamilton Analyzing Auditory Neurons by Learning Distance Functions
Inna Weiner, Tomer Hertz, Israel Nelken, Daphna Weinshall Bayesian Model Learning in Human Visual Perception
Gergő Orbán, Jozsef Fiser, Richard N Aslin, Máté Lengyel Bayesian Models of Human Action Understanding
Chris Baker, Rebecca Saxe, Joshua B. Tenenbaum Bayesian Sets
Zoubin Ghahramani, Katherine A. Heller Conditional Visual Tracking in Kernel Space
Cristian Sminchisescu, Atul Kanujia, Zhiguo Li, Dimitris Metaxas Consensus Propagation
Benjamin V. Roy, Ciamac C. Moallemi Context as Filtering
Daichi Mochihashi, Yuji Matsumoto Convex Neural Networks
Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte Correlated Topic Models
John D. Lafferty, David M. Blei Cue Integration for Figure/Ground Labeling
Xiaofeng Ren, Jitendra Malik, Charless C. Fowlkes Cyclic Equilibria in Markov Games
Martin Zinkevich, Amy Greenwald, Michael L. Littman Describing Visual Scenes Using Transformed Dirichlet Processes
Antonio Torralba, Alan S. Willsky, Erik B. Sudderth, William T. Freeman Dual-Tree Fast Gauss Transforms
Dongryeol Lee, Andrew W. Moore, Alexander G. Gray Efficient Estimation of OOMs
Herbert Jaeger, Mingjie Zhao, Andreas Kolling Extracting Dynamical Structure Embedded in Neural Activity
Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani Fast Krylov Methods for N-Body Learning
Nando D. Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang Gaussian Process Dynamical Models
Jack Wang, Aaron Hertzmann, David J Fleet Gaussian Processes for Multiuser Detection in CDMA Receivers
Juan J. Murillo-fuentes, Sebastian Caro, Fernando Pérez-Cruz Generalization to Unseen Cases
Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri Integrate-and-Fire Models with Adaptation Are Good Enough
Renaud Jolivet, Alexander Rauch, Hans-rudolf Lüscher, Wulfram Gerstner Kernelized Infomax Clustering
David Barber, Felix V. Agakov Kernels for Gene Regulatory Regions
Jean-philippe Vert, Robert Thurman, William S. Noble Large-Scale Multiclass Transduction
Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan Layered Dynamic Textures
Antoni B. Chan, Nuno Vasconcelos Learning Depth from Single Monocular Images
Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng Learning from Data of Variable Quality
Koby Crammer, Michael Kearns, Jennifer Wortman Learning Influence Among Interacting Markov Chains
Dong Zhang, Daniel Gatica-perez, Samy Bengio, Deb Roy Learning Minimum Volume Sets
Clayton Scott, Robert Nowak Learning Rankings via Convex Hull Separation
Glenn Fung, Rómer Rosales, Balaji Krishnapuram Modeling Neuronal Interactivity Using Dynamic Bayesian Networks
Lei Zhang, Dimitris Samaras, Nelly Alia-klein, Nora Volkow, Rita Goldstein Nested Sampling for Potts Models
Iain Murray, David MacKay, Zoubin Ghahramani, John Skilling Noise and the Two-Thirds Power Law
Uri Maoz, Elon Portugaly, Tamar Flash, Yair Weiss Non-Gaussian Component Analysis: A Semi-Parametric Framework for Linear Dimension Reduction
Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny, Klaus-Robert Müller Non-Local Manifold Parzen Windows
Yoshua Bengio, Hugo Larochelle, Pascal Vincent Off-Policy Learning with Options and Recognizers
Doina Precup, Cosmin Paduraru, Anna Koop, Richard S. Sutton, Satinder P. Singh Off-Road Obstacle Avoidance Through End-to-End Learning
Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp, Yann L. Cun Optimal Cue Selection Strategy
Vidhya Navalpakkam, Laurent Itti Optimizing Spatio-Temporal Filters for Improving Brain-Computer Interfacing
Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus-Robert Müller Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
Jo-anne Ting, Aaron D'souza, Kenji Yamamoto, Toshinori Yoshioka, Donna Hoffman, Shinji Kakei, Lauren Sergio, John Kalaska, Mitsuo Kawato Products of ``Edge-Perts
Max Welling, Peter V. Gehler Q-Clustering
Mukund Narasimhan, Nebojsa Jojic, Jeff A. Bilmes Query by Committee Made Real
Ran Gilad-bachrach, Amir Navot, Naftali Tishby Recovery of Jointly Sparse Signals from Few Random Projections
Michael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk Robust Design of Biological Experiments
Patrick Flaherty, Adam Arkin, Michael I. Jordan Robust Fisher Discriminant Analysis
Seung-jean Kim, Alessandro Magnani, Stephen Boyd Soft Clustering on Graphs
Kai Yu, Shipeng Yu, Volker Tresp Statistical Convergence of Kernel CCA
Kenji Fukumizu, Arthur Gretton, Francis R. Bach Structured Prediction via the Extragradient Method
Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan Temporally Changing Synaptic Plasticity
Minija Tamosiunaite, Bernd Porr, Florentin Wörgötter Tensor Subspace Analysis
Xiaofei He, Deng Cai, Partha Niyogi The Information-Form Data Association Filter
Brad Schumitsch, Sebastian Thrun, Gary Bradski, Kunle Olukotun Two View Learning: SVM-2K, Theory and Practice
Jason Farquhar, David Hardoon, Hongying Meng, John S. Shawe-taylor, Sándor Szedmák Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery
Jeremy Kubica, Joseph Masiero, Robert Jedicke, Andrew Connolly, Andrew W. Moore Variational EM Algorithms for Non-Gaussian Latent Variable Models
Jason Palmer, Kenneth Kreutz-Delgado, Bhaskar D. Rao, David P. Wipf Worst-Case Bounds for Gaussian Process Models
Sham M. Kakade, Matthias W. Seeger, Dean P. Foster