Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference (Hardcover)

Sebastian Thrun, Lawrence K. Saul, Bernhard Schlkopf

  • 出版商: MIT
  • 出版日期: 2004-06-04
  • 定價: $1,800
  • 售價: 1.7$299
  • 語言: 英文
  • 頁數: 1728
  • 裝訂: Hardcover
  • ISBN: 0262201526
  • ISBN-13: 9780262201520

立即出貨(限量) (庫存=5)

商品描述

Description:

The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.

Sebastian Thrun is Associate Professor in the Computer Science Department at Stanford University and Director of the Stanford AI Lab.

Lawrence K. Saul is Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania and General Chair of the 2004 NIPS conference.

Bernhard Schölkopf is Director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, and Professor at the Technical University in Berlin.

 

 

Table of Contents:

Preface xvii
NIPS Committees xxi
Reviewers xxiii
I Algorithms and Architectures
Efficient Multiscale Sampling from Products of Gaussian Mixtures
Alexander T. Ihler, Erik B. Sudderth, William T. Freeman and Alan S. Willsky
1
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
Mark Girolami and Ata Kaban
9
Hierarchical Topic Models and the Nested Chinese Restaurant Process
David M. Blei, Thomas L. Griffiths, Joshua B. Tenenbaum and Michael I. Jordan
17
Max-Margin Markov Networks
Benjamin Taskar, Carlos Guestrin and Daphne Koller
25
Invariant Pattern Recognition by Semi-Definite Programming Machines
Thore Graepel and Ralf Herbrich
33
Learning a Distance Metric from Relative Comparisons
Matthew Schultz and Thorsten Joachims
41
1-norm Support Vector Machines
Ji Zhu, Saharon Rosset, Trevor Hastie and Robert Tibshirani
49
Image Reconstruction by Linear Programming
Koji Tsuda and Gunnar Rätsch
57
Multiple-Instance Learning via Disjunctive Programming Boosting
Stuart Andrews and Thomas Hofmann
65
Convex Methods for Transduction
Tijl De Bie and Nello Cristianini
73
Kernel Dimensionality Reduction for Supervised Learning
Kenji Fukumizu, Francis R. Bach and Michael I. Jordan
81
Clustering with the Connectivity Kernel
Bernd Fischer, Volker Roth and Joachim M. Buhmann
89
Efficient and Robust Feature Extraction by Maximum Margin Criterion
Haifeng Li, Tao Jiang and Keshu Zhang
97
Sparse Greedy Minimax Probability Machine Classification
Thomas Strohmann, Andrei Belitski, Greg Grudic and Dennis DeCoste
105
Sequential Bayesian Kernel Regression
Jaco Vermaak, Simon J. Godsill and Arnaud Doucet
113
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms
Claudio Gentile
121
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
Liva Ralaivola and Florence d'Alché-Buc
129
Extreme Components Analysis
Max Welling, Felix Agakov and Christopher K. I. Williams
137
Linear Dependent Dimensionality Reduction
Nathan Srebro and Tommi Jaakkola
145
Locality Preserving Projections
Xiaofei He and Partha Niyogi
153
Optimal Manifold Representation of Data: An Information Theoretic Approach
Denis V. Chigirev and William Bialek
161
Ranking on Data Manifolds
Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet and Bernhard Schölkopf
169
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux and Marie Ouimet
177
Pairwise Clustering and Graphical Models
Noam Shental, Assaf Zomet, Tomer Hertz and Yair Weiss
185
Tree-structured Approximations by Expectation Propagation
Thomas Minka and Yuan Qi
193
The IM Algorithm: A Variational Approach to Information Maximization
David Barber and Felix Agakov
201
Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian-Vector Multiply
Eiji Mizutani and James W. Demmel
209
Large Scale Online Learning
Léon Bottou and Yann Le Cun
217
Online Classification on a Budget
Koby Crammer, Jaz Kandola and Yoram Singer
225
Online Learning via Global Feedback for Phrase Recognition
Xavier Carreras and Lluis Marquez
233
Sparse Representation and Its Applications in Blind Source Separation
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Sergei Shishkin, Jianting Cao and Fanji Gu
241
Perspectives on Sparse Bayesian Learning
David Wipf, Jason Palmer and Bhaskar D. Rao
249
Semi-Supervised Learning with Trees
Charles Kemp, Thomas L. Griffiths, Sean Stromsten and Joshua B. Tenenbaum
257
Efficient Exact k-NN and Nonparametric Classification in High Dimensions
Ting Liu, Andrew W. Moore and Alexander Gray
265
Nonstationary Covariance Functions for Gaussian Process Regression
Christopher J. Paciorek and Mark J. Schervish
273
Learning the k in k-means
Greg Hamerly and Charles Elkan
281
Finding the M Most Probable Configurations in Arbitrary Graphical Models
Chen Yanover and Yair Weiss
289
Non-linear CCA and PCA by Alignment of Local Models
Jakob J. Verbeek, Sam T. Roweis and Nikos Vlassis
297
Learning Spectral Clustering
Francis R. Bach and Michael I. Jordan
305
AUC Optimization vs. Error Rate Minimization
Corinna Cortes and Mehryar Mohri
313
Learning with Local and Global Consistency
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston and Bernhard Schölkopf
321
Gaussian Process Latent Variable Models for Visualization of High Dimensional Data
Neil D. Lawrence
329
Warped Gaussian Processes
Edward Snelson, Carl Edward Rasmussen and Zoubin Ghahramani
337
Can We Learn to Beat the Best Stock
Allan Borodin, Ran El-Yaniv and Vincent Gogan
345
Approximate Expectation Maximization
Tom Heskes, Onno Zoeter and Wim Wiegerinck
353
Linear Response for Approximate Inference
Max Welling and Yee Whye Teh
361
Semidefinite Relaxations for Approximate Inference on Graphs with Cycles
Martin Wainwright and Michael I. Jordan
369
Approximability of Probability Distributions
Alina Beygelzimer and Irina Rish
377
Denoising and Untangling Graphs Using Degree Priors
Quaid D. Morris and Brendan J. Frey
385
On the Concentration of Expectation and Approximate Inference in Layered Networks
XuanLong Nguyen and Michael I. Jordan
393
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
Radford M. Neal, Matthew J. Beal and Sam T. Roweis
401
Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis
Pedro F. Felzenszwalb, Daniel P. Huttenlocher and Jon M. Kleinberg
409
Wormholes Improve Contrastive Divergence
Geoffrey Hinton, Max Welling and Andriy Mnih
417
Sample Propagation
Mark A. Paskin
425
Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data
Amos J. Storkey
433
Laplace Propagation
Alexander Smola, Vishy Vishwanathan and Eleazar Eskin
441
Learning to Find Pre-Images
Geokhan H. Bakir, Jason Weston and Bernhard Schölkopf
449
Semi-Definite Programming by Perceptron Learning
Thore Graepel, Ralf Herbrich, Andriy Kharechko and John Shawe-Taylor
457
Computing Gaussian Mixture Models with EM Using Equivalence Constraints
Noam Shental, Aharon Bar-Hillel, Tomer Hertz and Daphna Weinshall
465
Feature Selection in Clustering Problems
Volker Roth and Tilman Lange
473
An Iterative Improvement Procedure for Hierarchical Clustering
David Kauchak and Sanjoy Dasgupta
481
Identifying Structure across Pre-Partitioned Data
Zvika Marx, Ido Dagan and Eli Shamir
489
Log-Linear Models for Label Ranking
Ofer Dekel, Christopher Manning and Yoram Singer
497
Minimax Embeddings
Matthew Brand
505
No Unbiased Estimator of the Variance of K-Fold Cross-Validation
Yoshua Bengio and Yves Grandvalet
513
Bias-Corrected Bootstrap and Model Uncertainty
Harald Steck and Tommi Jaakkola
521
Probability Estimates for Multi-Class Classification by Pairwise Coupling
Ting-Fan Wu, Chih-Jen Lin and Ruby C. Weng
529
Necessary Intransitive Likelihood-Ratio Classifiers
Gang Ji and Jeff Bilmes
537
Classification with Hybrid Generative/Discriminative Models
Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum
545
A Model for Learning the Semantics of Pictures
Victor Lavrenko, R. Manmatha and Jiwoon Jeon
553
Algorithms for Interdependent Security Games
Michael Kearns and Luis Ortiz
561
II Applications
Fast Embedding of Sparse Similarity Graphs
John C. Platt
571
GPPS: A Gaussian Process Positioning System for Cellular Networks
Anton Schwaighofer, Marian Grigoras, Volker Tresp and Clemens Hoffmann
579
An Autonomous Robotic System for Mapping Abandoned Mines
David Ferguson, Aaron Morris, Dirk Hähnel, Christopher Baker, Zachary Omohundro, Carlos Reverte, Scott Thayer, William Whittaker, Wolfram Burgard and Sebastian Thrun
587
Semi-supervised Protein Classification Using Cluster Kernels
Jason Weston, Christina Leslie, Dengyong Zhou, André Elisseeff and William S. Noble
595
Statistical Debugging of Sampled Programs
Alice X. Zheng, Michael I. Jordan, Ben Liblit and Alex Aiken
603
Markov Models for Automated ECG Interval Analysis
Nicholas P. Hughes, Lionel Tarassenko and Stephen Roberts
611
Parameterized Novelty Detectors for Environmental Sensor Monitoring
Cynthia Archer, Todd K. Leen and Antonio Baptista
619
Modeling User Rating Profiles for Collaborative Filtering
Benjamin Marlin
627
Application of SVMs for Colour Classification and Collision Detection with AIBO Robots
Michael J. Quinlan, Stephan K. Chalup and Richard H. Middleton
635
Kernels for Structured Natural Language Data
Jun Suzuki, Yutaka Sasaki and Eisaku Maeda
643
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters
Daniel B. Neill and Andrew W. Moore
651
Link Prediction in Relational Data
Benjamin Taskar, Ming-Fai Wong, Pieter Abbeel and Daphne Koller
659
Unsupervised Color Decomposition of Histologically Stained Tissue Samples
Andrew Rabinovich, Sameer Agarwal, Casey Laris, Jeffrey H. Price and Serge J. Belongie
667
ICA-based Clustering of Genes from Microarray Expression Data
Su-In Lee and Serafim Batzoglou
675
Gene Expression Clustering with Functional Mixture Models
Darya Chudova, Christopher Hart, Eric Mjolsness and Padhraic Smyth
683
III Brain Imaging
Reconstructing MEG Sources with Unknown Correlations
Maneesh Sahani and Srikantan Nagarajan
693
Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales
Saori C. Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto and Shigeto Yamawaki
701
Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects
Xuerui Wang, Rebecca Hutchinson and Tom M. Mitchell
709
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Roland Vollgraf, Michael Scholz, Ian A. Meinertzhagen and Klaus Obermayer
717
Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface
Yu Zhou, Steven G. Mason and Gary E. Birch
725
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class
Guido Dornhege, Benjamin Blankertz, Gabriel Curio and Klaus-Robert Müller
733
Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron
Sung C. Jun and Barak A. Pearlmutter
741
IV Control and Reinforcement Learning
Gaussian Processes in Reinforcement Learning
Carl Edward Rasmussen and Malte Kuss
751
Applying Metric-Trees to Belief-Point POMDPs
Jolette Pineau, Geoffrey J. Gordon and Sebastian Thrun
759
ARA*: Anytime A* with Provable Bounds on Sub-Optimality
Maxim Likhachev, Geoffrey J. Gordon and Sebastian Thrun
767
Approximate Planning in POMDPs with Macro-Actions
Georgios Theocharous and Leslie Pack Kaelbling
775
Envelope-based Planning in Relational MDPs
Natalia H. Gardiol and Leslie Pack Kaelbling
783
An MDP-Based Approach to Online Mechanism Design
David C. Parkes and Satinder P. Singh
791
Autonomous Helicopter Flight via Reinforcement Learning
Andrew Y. Ng, H. Jin Kim, Michael I. Jordan and Shankar Sastry
799
All learning is Local: Multi-agent Learning in Global Reward Games
Yu-Han Chang, Tracey Ho and Leslie Pack Kaelbling
807
How to Combine Expert (and Novice) Advice when Actions Impact the Environment?
Daniela Pucci de Farias and Nimrod Megiddo
815
Bounded Finite State Controllers
Pascal Poupart and Craig Boutilier
823
Policy Search by Dynamic Programming
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng and Jeff Schneider
831
Robustness in Markov Decision Problems with Uncertain Transition Matrices
Arnab Nilim and Laurent El Ghaoui
839
Approximate Policy Iteration with a Policy Language Bias
Alan Fern, Sungwook Yoon and Robert Givan
847
A Nonlinear Predictive State Representation
Matthew R. Rudary and Satinder P. Singh
855
Learning Near-Pareto-Optimal Conventions in Polynomial Time
XiaoFeng Wang and Tuomas Sandholm
863
Extending Q-Learning to General Adaptive Multi-Agent Systems
Gerald Tesauro
871
Auction Mechanism Design for Multi-Robot Coordination
Curt Bererton, Geoffrey J. Gordon and Sebastian Thrun
879
Distributed Optimization in Adaptive Networks
Ciamac C. Moallemi and Benjamin Van Roy
887
Linear Program Approximations for Factored Continuous-State Markov Decision Processes
Milos Hauskrecht and Branislav Kveton
895
V Cognitive Science and Artificial Intelligence
Insights from Machine Learning Applied to Human Visual Classification
Arnulf B. A. Graf and Felix A. Wichmann
905
Sensory Modality Segregation
Virginia de Sa
913
Reasoning about Time and Knowledge in Neural Symbolic Learning Systems
Artur S. d'Avila Garcez and Luis C. Lamb
921
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
Marc Toussaint
929
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science
Woojae Kim, Daniel J. Navarro, Mark A. Pitt and In Jae Myung
937
Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and Effectors
D. Philipona, J. Kevin O'Regan, J.-P. Nadal and Olivier Coenen
945
From Algorithmic to Subjective Randomness
Thomas L. Griffiths and Joshua B. Tenenbaum
953