NIPS 2005 Proceedings

Advances in Neural Information Processing Systems 18 (NIPS 2005)

The papers below appear in Advances in Neural Information Processing Systems 18 edited by Y. Weiss and B. Schölkopf and J.C. Platt.
They are proceedings from the conference, "Neural Information Processing Systems 2005."

Learning vehicular dynamics, with application to modeling helicopters Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng
Policy-Gradient Methods for Planning Douglas Aberdeen
Kernelized Infomax Clustering David Barber, Felix V. Agakov
Large-scale biophysical parameter estimation in single neurons via constrained linear regression Misha Ahrens, Liam Paninski, Quentin J. Huys
Maximum Margin Semi-Supervised Learning for Structured Variables Y. Altun, D. McAllester, M. Belkin
Large scale networks fingerprinting and visualization using the k-core decomposition J. I. Alvarez-hamelin, Luca Dall'asta, Alain Barrat, Alessandro Vespignani
Fast Information Value for Graphical Models Brigham S. Anderson, Andrew W. Moore
A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects David Arathorn
Combining Graph Laplacians for Semi--Supervised Learning Andreas Argyriou, Mark Herbster, Massimiliano Pontil
Learning in Silicon: Timing is Everything John V. Arthur, Kwabena Boahen
Learning Topology with the Generative Gaussian Graph and the EM Algorithm Michaël Aupetit
On Local Rewards and Scaling Distributed Reinforcement Learning Drew Bagnell, Andrew Y. Ng
Bayesian models of human action understanding Chris Baker, Rebecca Saxe, Joshua B. Tenenbaum
The Curse of Highly Variable Functions for Local Kernel Machines Yoshua Bengio, Olivier Delalleau, Nicolas L. Roux
Non-Local Manifold Parzen Windows Yoshua Bengio, Hugo Larochelle, Pascal Vincent
Convex Neural Networks Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny, Klaus-Robert Müller
From Weighted Classification to Policy Search Doron Blatt, Alfred O. Hero
Correlated Topic Models John D. Lafferty, David M. Blei
Saliency Based on Information Maximization Neil Bruce, John Tsotsos
Active Learning For Identifying Function Threshold Boundaries Brent Bryan, Robert C. Nichol, Christopher R. Genovese, Jeff Schneider, Christopher J. Miller, Larry Wasserman
Subsequence Kernels for Relation Extraction Raymond J. Mooney, Razvan C. Bunescu
Faster Rates in Regression via Active Learning Rebecca Willett, Robert Nowak, Rui M. Castro
Gradient Flow Independent Component Analysis in Micropower VLSI Abdullah Celik, Milutin Stanacevic, Gert Cauwenberghs
Improved risk tail bounds for on-line algorithms Nicolò Cesa-bianchi, Claudio Gentile
Layered Dynamic Textures Antoni B. Chan, Nuno Vasconcelos
Size Regularized Cut for Data Clustering Yixin Chen, Ya Zhang, Xiang Ji
Learning from Data of Variable Quality Koby Crammer, Michael Kearns, Jennifer Wortman
Efficient estimation of hidden state dynamics from spike trains Marton G. Danoczy, Richard H. R. Hahnloser
Coarse sample complexity bounds for active learning Sanjoy Dasgupta
Norepinephrine and Neural Interrupts Peter Dayan, Angela J. Yu
Fast Krylov Methods for N-Body Learning Nando D. Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang
The Forgetron: A Kernel-Based Perceptron on a Fixed Budget Ofer Dekel, Shai Shalev-shwartz, Yoram Singer
Data-Driven Online to Batch Conversions Ofer Dekel, Yoram Singer
Beyond Gaussian Processes: On the Distributions of Infinite Networks Ricky Der, Daniel D. Lee
Generalized Nonnegative Matrix Approximations with Bregman Divergences Suvrit Sra, Inderjit S. Dhillon
An Application of Markov Random Fields to Range Sensing James Diebel, Sebastian Thrun
Transfer learning for text classification Chuong B. Do, Andrew Y. Ng
A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels Eizaburo Doi, Doru C. Balcan, Michael S. Lewicki
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus-Robert Müller
Correcting sample selection bias in maximum entropy density estimation Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
Searching for Character Models Jaety Edwards, David Forsyth
Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps Austin I. Eliazar, Ronald Parr
Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods Yaakov Engel, Peter Szabo, Dmitry Volkinshtein
Two view learning: SVM-2K, Theory and Practice Jason Farquhar, David Hardoon, Hongying Meng, John S. Shawe-taylor, Sándor Szedmák
Robust design of biological experiments Patrick Flaherty, Adam Arkin, Michael I. Jordan
Pattern Recognition from One Example by Chopping Francois Fleuret, Gilles Blanchard
Mixture Modeling by Affinity Propagation Brendan J. Frey, Delbert Dueck
Statistical Convergence of Kernel CCA Kenji Fukumizu, Arthur Gretton, Francis R. Bach
Learning Rankings via Convex Hull Separation Glenn Fung, Rómer Rosales, Balaji Krishnapuram
A Connectionist Model for Constructive Modal Reasoning Artur Garcez, Luis C. Lamb, Dov M. Gabbay
Large-Scale Multiclass Transduction Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan
Products of ``Edge-perts Max Welling, Peter V. Gehler
Fast biped walking with a reflexive controller and real-time policy searching Tao Geng, Bernd Porr, Florentin Wörgötter
Bayesian Sets Zoubin Ghahramani, Katherine A. Heller
Query by Committee Made Real Ran Gilad-bachrach, Amir Navot, Naftali Tishby
Metric Learning by Collapsing Classes Amir Globerson, Sam T. Roweis
Interpolating between types and tokens by estimating power-law generators Sharon Goldwater, Mark Johnson, Thomas L. Griffiths
A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification Yves Grandvalet, Johnny Mariethoz, Samy Bengio
Infinite latent feature models and the Indian buffet process Zoubin Ghahramani, Thomas L. Griffiths
Computing the Solution Path for the Regularized Support Vector Regression Lacey Gunter, Ji Zhu
Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs Firas Hamze, Nando de Freitas
Tensor Subspace Analysis Xiaofei He, Deng Cai, Partha Niyogi
Laplacian Score for Feature Selection Xiaofei He, Deng Cai, Partha Niyogi
Inferring Motor Programs from Images of Handwritten Digits Vinod Nair, Geoffrey E. Hinton
Response Analysis of Neuronal Population with Synaptic Depression Wentao Huang, Licheng Jiao, Shan Tan, Maoguo Gong
Non-iterative Estimation with Perturbed Gaussian Markov Processes Yunsong Huang, B. Keith Jenkins
Learning Cue-Invariant Visual Responses Jarmo Hurri
Bayesian Surprise Attracts Human Attention Laurent Itti, Pierre F. Baldi
Efficient Estimation of OOMs Herbert Jaeger, Mingjie Zhao, Andreas Kolling
Representing Part-Whole Relationships in Recurrent Neural Networks Viren Jain, Valentin Zhigulin, H. S. Seung
A Probabilistic Approach for Optimizing Spectral Clustering Rong Jin, Feng Kang, Chris H. Ding
Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation Dmitry Malioutov, Alan S. Willsky, Jason K. Johnson
Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails Nebojsa Jojic, Vladimir Jojic, Christopher Meek, David Heckerman, Brendan J. Frey
Integrate-and-Fire models with adaptation are good enough Renaud Jolivet, Alexander Rauch, Hans-rudolf Lüscher, Wulfram Gerstner
Generalization Error Bounds for Aggregation by Mirror Descent with Averaging Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov, Nicolas Vayatis
From Batch to Transductive Online Learning Sham Kakade, Adam Tauman Kalai
Worst-Case Bounds for Gaussian Process Models Sham M. Kakade, Matthias W. Seeger, Dean P. Foster
Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification Ashish Kapoor, Hyungil Ahn, Yuan Qi, Rosalind W. Picard
Is Early Vision Optimized for Extracting Higher-order Dependencies? Yan Karklin, Michael S. Lewicki
A matching pursuit approach to sparse Gaussian process regression Sathiya Keerthi, Wei Chu
Benchmarking Non-Parametric Statistical Tests Mikaela Keller, Samy Bengio, Siew Y. Wong
Robust Fisher Discriminant Analysis Seung-jean Kim, Alessandro Magnani, Stephen Boyd
Measuring Shared Information and Coordinated Activity in Neuronal Networks Kristina Klinkner, Cosma Shalizi, Marcelo Camperi
Inference with Minimal Communication: a Decision-Theoretic Variational Approach O. P. Kreidl, Alan S. Willsky
Generalization in Clustering with Unobserved Features Eyal Krupka, Naftali Tishby
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery Jeremy Kubica, Joseph Masiero, Robert Jedicke, Andrew Connolly, Andrew W. Moore
Assessing Approximations for Gaussian Process Classification Malte Kuss, Carl E. Rasmussen
Rodeo: Sparse Nonparametric Regression in High Dimensions Larry Wasserman, John D. Lafferty
Fixing two weaknesses of the Spectral Method Kevin Lang
Fusion of Similarity Data in Clustering Tilman Lange, Joachim M. Buhmann
A PAC-Bayes approach to the Set Covering Machine François Laviolette, Mario Marchand, Mohak Shah
Off-Road Obstacle Avoidance through End-to-End Learning Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp, Yann L. Cun
Dual-Tree Fast Gauss Transforms Dongryeol Lee, Andrew W. Moore, Alexander G. Gray
CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits Jung Hoon Lee, Xiaolong Ma, Konstantin K. Likharev
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity Robert A. Legenstein, Wolfgang Maass
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches Anna Levina, Michael Herrmann
From Lasso regression to Feature vector machine Fan Li, Yiming Yang, Eric P. Xing
Location-based activity recognition Lin Liao, Dieter Fox, Henry Kautz
Radial Basis Function Network for Multi-task Learning Xuejun Liao, Lawrence Carin
Asymptotics of Gaussian Regularized Least Squares Ross Lippert, Ryan Rifkin
Efficient Unsupervised Learning for Localization and Detection in Object Categories Nicolas Loeff, Himanshu Arora, Alexander Sorokin, David Forsyth
Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
Ideal Observers for Detecting Motion: Correspondence Noise Hongjing Lu, Alan L. Yuille
Principles of real-time computing with feedback applied to cortical microcircuit models Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Sridhar Mahadevan, Mauro Maggioni
Noise and the two-thirds power Law Uri Maoz, Elon Portugaly, Tamar Flash, Yair Weiss
Modeling Memory Transfer and Saving in Cerebellar Motor Learning Naoki Masuda, Shun-ichi Amari
An exploration-exploitation model based on norepinepherine and dopamine activity Samuel M. McClure, Mark S. Gilzenrat, Jonathan D. Cohen
Online Discovery and Learning of Predictive State Representations Peter Mccracken, Michael Bowling
An Alternative Infinite Mixture Of Gaussian Process Experts Edward Meeds, Simon Osindero
Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments Keiji Miura, Masato Okada, Shun-ichi Amari
Consensus Propagation Benjamin V. Roy, Ciamac C. Moallemi
Context as Filtering Daichi Mochihashi, Yuji Matsumoto
Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms Baback Moghaddam, Yair Weiss, Shai Avidan
Top-Down Control of Visual Attention: A Rational Account Michael Shettel, Shaun Vecera, Michael C. Mozer
Rate Distortion Codes in Sensor Networks: A System-level Analysis Tatsuto Murayama, Peter Davis
Gaussian Processes for Multiuser Detection in CDMA receivers Juan J. Murillo-fuentes, Sebastian Caro, Fernando Pérez-Cruz
Nested sampling for Potts models Iain Murray, David MacKay, Zoubin Ghahramani, John Skilling
Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators Boaz Nadler, Stephane Lafon, Ioannis Kevrekidis, Ronald R. Coifman
Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity Kenneth Hild, Kensuke Sekihara, Hagai T. Attias, Srikantan S. Nagarajan
An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Architecture Yusuke Nakashita, Yoshio Mita, Tadashi Shibata
Q-Clustering Mukund Narasimhan, Nebojsa Jojic, Jeff A. Bilmes
Optimal cue selection strategy Vidhya Navalpakkam, Laurent Itti
Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity Amir Navot, Lavi Shpigelman, Naftali Tishby, Eilon Vaadia
A Bayesian Spatial Scan Statistic Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper
Divergences, surrogate loss functions and experimental design XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
How fast to work: Response vigor, motivation and tonic dopamine Yael Niv, Nathaniel D. Daw, Peter Dayan
Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction Guido Nolte, Andreas Ziehe, Frank Meinecke, Klaus-Robert Müller
An Approximate Inference Approach for the PCA Reconstruction Error Manfred Opper
Bayesian model learning in human visual perception Gergő Orbán, Jozsef Fiser, Richard N. Aslin, Máté Lengyel
Spiking Inputs to a Winner-take-all Network Matthias Oster, Shih-Chii Liu
Variational EM Algorithms for Non-Gaussian Latent Variable Models Jason Palmer, Kenneth Kreutz-Delgado, Bhaskar D. Rao, David P. Wipf
Nonparametric inference of prior probabilities from Bayes-optimal behavior Liam Paninski
Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI Ofer Pasternak, Nathan Intrator, Nir Sochen, Yaniv Assaf
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects Jean-pascal Pfister, Wulfram Gerstner
Scaling Laws in Natural Scenes and the Inference of 3D Shape Tai-sing Lee, Brian R. Potetz
Off-policy Learning with Options and Recognizers Doina Precup, Cosmin Paduraru, Anna Koop, Richard S. Sutton, Satinder P. Singh
Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization Maxim Raginsky, Svetlana Lazebnik
Preconditioner Approximations for Probabilistic Graphical Models John D. Lafferty, Pradeep K. Ravikumar
Cue Integration for Figure/Ground Labeling Xiaofeng Ren, Jitendra Malik, Charless C. Fowlkes
Generalization to Unseen Cases Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
Visual Encoding with Jittering Eyes Michele Rucci
Dynamic Social Network Analysis using Latent Space Models Purnamrita Sarkar, Andrew W. Moore
Logic and MRF Circuitry for Labeling Occluding and Thinline Visual Contours Eric Saund
Learning Depth from Single Monocular Images Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng
Identifying Distributed Object Representations in Human Extrastriate Visual Cortex Rory Sayres, David Ress, Kalanit Grill-spector
On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal? Michael Schmitt, Laura Martignon
Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation Jin Yu, Douglas Aberdeen, Nicol N. Schraudolph
The Information-Form Data Association Filter Brad Schumitsch, Sebastian Thrun, Gary Bradski, Kunle Olukotun
A Bayesian Framework for Tilt Perception and Confidence Odelia Schwartz, Peter Dayan, Terrence J. Sejnowski
Learning Minimum Volume Sets Clayton Scott, Robert Nowak
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
Fast Gaussian Process Regression using KD-Trees Yirong Shen, Matthias Seeger, Andrew Y. Ng
Learning Shared Latent Structure for Image Synthesis and Robotic Imitation Aaron Shon, Keith Grochow, Aaron Hertzmann, Rajesh P. Rao
Selecting Landmark Points for Sparse Manifold Learning Jorge Silva, Jorge Marques, João Lemos
Conditional Visual Tracking in Kernel Space Cristian Sminchisescu, Atul Kanujia, Zhiguo Li, Dimitris Metaxas
Sparse Gaussian Processes using Pseudo-inputs Edward Snelson, Zoubin Ghahramani
Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface Le Song, Evian Gordon, Elly Gysels
A General and Efficient Multiple Kernel Learning Algorithm Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer
Prediction and Change Detection Mark Steyvers, Scott Brown
Sensory Adaptation within a Bayesian Framework for Perception Alan A. Stocker, Eero P. Simoncelli
Describing Visual Scenes using Transformed Dirichlet Processes Antonio Torralba, Alan S. Willsky, Erik B. Sudderth, William T. Freeman
Active Learning for Misspecified Models Masashi Sugiyama
Temporal Abstraction in Temporal-difference Networks Eddie Rafols, Anna Koop, Richard S. Sutton
Sequence and Tree Kernels with Statistical Feature Mining Jun Suzuki, Hideki Isozaki
Silicon growth cones map silicon retina Brian Taba, Kwabena Boahen
Temporally changing synaptic plasticity Minija Tamosiunaite, Bernd Porr, Florentin Wörgötter
Structured Prediction via the Extragradient Method Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan
Affine Structure From Sound Sebastian Thrun
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
Generalization error bounds for classifiers trained with interdependent data Nicolas Usunier, Massih-reza Amini, Patrick Gallinari
TD(0) Leads to Better Policies than Approximate Value Iteration Benjamin V. Roy
An aVLSI Cricket Ear Model Andre V. Schaik, Richard Reeve, Craig Jin, Tara Hamilton
Goal-Based Imitation as Probabilistic Inference over Graphical Models Deepak Verma, Rajesh P. Rao
Kernels for gene regulatory regions Jean-philippe Vert, Robert Thurman, William S. Noble
Consistency of one-class SVM and related algorithms Régis Vert, Jean-philippe Vert
Multiple Instance Boosting for Object Detection Cha Zhang, John C. Platt, Paul A. Viola
Estimating the wrong Markov random field: Benefits in the computation-limited setting Martin J. Wainwright
Recovery of Jointly Sparse Signals from Few Random Projections Michael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk
Gaussian Process Dynamical Models Jack Wang, Aaron Hertzmann, David J. Fleet
Group and Topic Discovery from Relations and Their Attributes Xuerui Wang, Natasha Mohanty, Andrew McCallum
A Bayes Rule for Density Matrices Manfred K. Warmuth
Variational Bayesian Stochastic Complexity of Mixture Models Kazuho Watanabe, Sumio Watanabe
Distance Metric Learning for Large Margin Nearest Neighbor Classification Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul
Analyzing Auditory Neurons by Learning Distance Functions Inna Weiner, Tomer Hertz, Israel Nelken, Daphna Weinshall
Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games Gabriel Y. Weintraub, Lanier Benkard, Benjamin Van Roy
Active Bidirectional Coupling in a Cochlear Chip Bo Wen, Kwabena A. Boahen
Neural mechanisms of contrast dependent receptive field size in V1 Jim Wielaard, Paul Sajda
Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care Christopher Williams, John Quinn, Neil Mcintosh
Comparing the Effects of Different Weight Distributions on Finding Sparse Representations Bhaskar D. Rao, David P. Wipf
Message passing for task redistribution on sparse graphs K. Y. Michael Wong, David Saad, Zhuo Gao
Modeling Neural Population Spiking Activity with Gibbs Distributions Frank Wood, Stefan Roth, Michael J. Black
Extracting Dynamical Structure Embedded in Neural Activity Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani
Soft Clustering on Graphs Kai Yu, Shipeng Yu, Volker Tresp
Augmented Rescorla-Wagner and Maximum Likelihood Estimation Alan L. Yuille
The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search Gregory Zelinsky, Wei Zhang, Bing Yu, Xin Chen, Dimitris Samaras
Learning Influence among Interacting Markov Chains Dong Zhang, Daniel Gatica-perez, Samy Bengio, Deb Roy
Learning Multiple Related Tasks using Latent Independent Component Analysis Jian Zhang, Zoubin Ghahramani, Yiming Yang
Modeling Neuronal Interactivity using Dynamic Bayesian Networks Lei Zhang, Dimitris Samaras, Nelly Alia-klein, Nora Volkow, Rita Goldstein
Analysis of Spectral Kernel Design based Semi-supervised Learning Tong Zhang, Rie Kubota Ando
A Computational Model of Eye Movements during Object Class Detection Wei Zhang, Hyejin Yang, Dimitris Samaras, Gregory J. Zelinsky
Separation of Music Signals by Harmonic Structure Modeling Yun-gang Zhang, Chang-shui Zhang
A Domain Decomposition Method for Fast Manifold Learning Zhenyue Zhang, Hongyuan Zha
A Hierarchical Compositional System for Rapid Object Detection Long Zhu, Alan L. Yuille
Cyclic Equilibria in Markov Games Martin Zinkevich, Amy Greenwald, Michael L. Littman
On the Convergence of Eigenspaces in Kernel Principal Component Analysis Laurent Zwald, Gilles Blanchard