Advances in Neural Information Processing Systems 17 : Proceedings of the 2004 Conference (Hardcover)

Lawrence K. Saul, Yair Weiss, Lon Bottou

  • 出版商: MIT
  • 出版日期: 2005-05-20
  • 售價: $1,800
  • 貴賓價: 9.8$1,764
  • 語言: 英文
  • 頁數: 1696
  • 裝訂: Hardcover
  • ISBN: 0262195348
  • ISBN-13: 9780262195348
  • 相關分類: 人工智慧Machine Learning
  • 立即出貨

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Description:

The annual Neural Information Processing Systems (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 twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.

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.

Yair Weiss is Senior Lecturer in the School of Computer Science and Engineering at The Hebrew University of Jerusalem and Program Chair of the 2004 NIPS conference.

Léon Bottou is Senior Research Scientist at NEC Laboratories America in Princeton, New Jersey, and Publications Chair of the 2004 NIPS conference.

 

Table of Contents:

Contents v
Preface xix
Donors xxi
NIPS foundation xxii
Committees xxiii
Reviewers xxiv
Learning first-order Markov models for control
Pieter Abbeel and Andrew Y. Ng
1
A Large Deviation Bound for the Area Under the ROC Curve
Shivani Agarwal, Thore Graepel, Ralf Herbrich and Dan Roth
9
Learning Preferences for Multiclass Problems
Fabio Aiolli and Alessandro Sperduti
17
Harmonising Chorales by Probabilistic Inference
Moray Allan and Christopher K. I. Williams
25
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung Pang, Daphne Koller, Sebastian Thrun and James Davis
33
A Direct Formulation for Sparse PCA Using Semidefinite Programming
Alexandre d'Aspremont, Laurent El Ghaoui, Michael I. Jordan and Gert R. G. Lanckriet
41
Comparing Beliefs, Surveys, and Random Walks
Erik Aurell, Uri Gordon and Scott Kirkpatrick
49
The power of feature clustering: An application to object detection
Shai Avidan and Moshe Butman
57
Blind One-microphone Speech Separation: A Spectral Learning Approach
Francis R. Bach and Michael I. Jordan
65
Computing regularization paths for learning multiple kernels
Francis R. Bach, Romain Thibaux and Michael I. Jordan
73
Breaking SVM Complexity with Cross-Training
Gökhan H. Bakir, Léon Bottou and Jason Weston
81
Co-Training and Expansion: Towards Bridging Theory and Practice
Maria-Florina Balcan, Avrim Blum and Ke Yang
89
Large-Scale Prediction of Disulphide Bond Connectivity
Pierre Baldi, Jianlin Cheng and Alessandro Vullo
97
Spike Sorting: Bayesian Clustering of Non-Stationary Data
Aharon Bar-Hillel, Adam Spiro and Eran Stark
105
Exponentiated Gradient Algorithms for Large-margin Structured Classification
Peter L. Bartlett, Michael Collins, Benjamin Taskar and David A. McAllester
113
Maximising Sensitivity in a Spiking Network
Anthony J. Bell and Lucas Parra
121
Non-Local Manifold Tangent Learning
Yoshua Bengio and Martin Monperrus
129
Who's in the Picture
Tamara L. Berg, Alexander C. Berg, Jaety Edwards and David Forsyth
137
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks
Nils Bertschinger, Thomas Natschläger and Robert A. Legenstein
145
A Second Order Cone programming Formulation for Classifying Missing Data
Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy and Alex Smola
153
Support Vector Classification with Input Data Uncertainty
Jinbo Bi and Tong Zhang
161
Responding to Modalities with Different Latencies
Fredrik Bissmarck, Hiroyuki Nakahara, Kenji Doya and Okihide Hikosaka
169
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
Tobias Blaschke and Laurenz Wiskott
177
Hierarchical Distributed Representations for Statistical Language Modeling
John Blitzer, Kilian Weinberger, Lawrence Saul and Fernando C. N. Pereira
185
Markov Networks for Detecting Overlapping Elements in Sequence Data
Joseph Bockhorst and Mark Craven
193
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity
Sander. M. Bohte and Michael C Mozer
201
Convergence and No-Regret in Multiagent Learning
Michael Bowling
209
Dependent Gaussian Processes
Phillip Boyle and Marcus Frean
217
Proximity Graphs for Clustering and Manifold Learning
Miguel A. Carreira-Perpinan and Richard S. Zemel
225
Incremental Algorithms for Hierarchical Classifications
Nicolò Cesa-Bianchi, Claudio Gentile, Andrea Tironi and Luca Zaniboni
233
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
Nicolò Cesa-Bianchi, Claudio Gentile and Luca Zaniboni
241
Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation
Shantanu Chakrabartty and Gert Cauwenberghs
249
A Machine Learning Approach to Conjoint Analysis
Olivier Chapelle and Zaid Harchaoui
257
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
Kumar Chellapilla and Patrice Y. Simard
265
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
Chakra Chennubhotla and Allan Jepson
273
Modeling Conversational Dynamics as a Mixed-Memory Markov Process
Tanzeem Choudhury and Sumit Basu
281
Theories of Access Consciousness
Michael D. Colagrosso and Michael C Mozer
289
Distributed Information Regularization on Graphs
Adrian Corduneanu and Tommi S. Jaakkola
297
Confidence Intervals for the Area Under the ROC Curve
Corinna Cortes and Mehryar Mohri
305
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account
Aaron C. Courville, Nathaniel D. Daw and David S. Touretzky
313
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM
Juan José del Coz, Gustavo F. Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde and Carlos Sañudo
321
Semigroup Kernals on Finite Sets
Marco Cuturi and Jean-Philippe Vert
329
Analysis of a greedy active learning strategy
Sanjoy Dasgupta
337
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees
Ofer Dekel, Shai Shalev-Shwartz and Yoram Singer
345
Bayesian inference in spiking neurons
Sophie Deneve
353
Triangle Fixing Algorithms for the Metric Nearness Problem
Inderjit S. Dhillon, Suvrit Sra and Joel Tropp
361
Pictorial Structures for Molecular Modeling: Interpreting Density Maps
Frank DiMaio, Jude Shavlik and George Phillips
369
Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units
Eizaburo Doi and Michael S. Lewicki
377
Making Latin Manuscripts Searchable using gHMM's
Jaety Edwards, Yee Whye Teh, David Forsyth, Roger Bock, Michael Maire and Grace Vesom
385
Seeing through Water
Alexei Efros, Volkan Isler, Jianbo Shi and Mirkó Visontai
393
Experts in a Markov Decision Process
Eyal Even-Dar, Sham Kakade and Yishay Mansour
401
Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments
Daniela Pucci de Farias and Nimrod Megiddo
409
A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees
Daniela Pucci de Farias and Benjamin Van Roy
417
Learning Hyper-Features for Visual Identification
Andras D. Ferencz, Erik G. Learned-Miller and Jitendra Malik
425
Sampling Methods for Unsupervised Learning
Rob Fergus, Andrew Zisserman and Pietro Perona
433
On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks
Miguel Figueroa, Seth Bridges and Chris Diorio
441
Object Classification from a Single Example Utilizing Class Relevance Metrics
Michael Fink
449
A Hidden Markov Model for de Novo Peptide Sequencing
Bernd Fischer, Volker Roth, Joachim M. Buhmann, Jonas Grossmann, Sacha Baginsky, Wilhelm Gruissem, Franz Roos and Peter Widmayer
457
Implicit Wiener Series for Higher-Order Image Analysis
Matthias O. Franz and Bernhard Schölkopf
465
Joint Probabilistic Curve Clustering and Alignment
Scott J. Gaffney and Padhraic Smyth
473
Discriminant Saliency for Visual Recognition from Cluttered Scenes
Dashan Gao and Nuno Vasconcelos
481
Instance-Based Relevance Feedback for Image Retrieval
Giorgio Giacinto and Fabio Roli
489
Euclidean Embedding of Co-Occurrence Data
Amir Globerson, Gal Chechik, Fernando C. N. Pereira and Naftali Tishby
497
Hierarchical Clustering of a Mixture Model
Jacob Goldberger and Sam T. Roweis
505
Neighbourhood Components Analysis
Jacob Goldberger, Sam T. Roweis, Geoffrey Hinton and Ruslan Salakhutdinov
513
Parallel Support Vector Machines: The Cascade SVM
Hans Peter Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic and Vladimir Vapnik
521
Semi-Supervised Learning by Entropy Minimization
Yves Grandvalet and Yoshua Bengio
529
Integrating Topics and Syntax
Thomas L. Griffiths, Mark Steyvers, David M. Blei and Joshua B. Tenenbaum
537
Result Analysis of the NIPS 2003 Feature Selection Challenge
Isabelle Guyon, Steve Gunn, Asa Ben-Hur and Gideon Dror
545
Theory of localized synfire chain: characteristic propagation speed of stable spike pattern
Kosuke Hamaguchi, Masato Okada and Kazuyuki Aihara
553
The Entire Regulation Path for the Support Vector Machine
Trevor Hastie, Saharon Rosset, Robert Tibshirani and Ji Zhu
561
An Auditory Paradigm for Brain-Computer Interfaces
N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Niels Birbaumer and Bernhard Schölkopf
569
The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning
Constanze Hofstoetter, Manuel Gil, Kynan Eng, Giacomo Indiveri, Matti Mintz, Jörg Kramer and Paul Verschure
577
Schema Learning: Experience-Based Construction of Predictive Action Models
Michael P. Holmes and Charles Lee Isbell, Jr.
585
Unsupervised Variational Bayesian Learning of Nonlinear Models
Antti Honkela and Harri Valpola
593
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill
Tzu-Kuo Huang, Chih-Jen Lin and Ruby C. Weng
601
Message Errors in Belief Propagation
Alexander T. Ihler, John W. Fisher and Alan S. Willsky
609
Parametric Embedding for Class Visualization
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths and Joshua B. Tenenbaum
617
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernal Feature Space
Robert Jenssen, Deniz Erdogmus, José C. Príncipe and Torbjørn Eltoft
625
Economic Properties of Social Networks
Sham Kakade, Michael Kearns, Luis Ortiz, Robin Pemantle and Siddharth Suri
633
Online Bounds for Bayesian Algorithms
Sham Kakade and Andrew Y. Ng
641
Maximal Margin Labeling for Multi-Topic Text Categorization
Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira and Eisaku Maeda
649
Generalization Error and Algorithmic Convergence of Median Boosting
Balázs Kégl
657
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
Balázs Kégl and Ligen Wang
665
Face Detection -- Efficient and Rank Deficient
Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz and Bernhard Schölkopf
673
Neural Networks Computation by In Vitro Transcriptional Circuits
Jongmin Kim, John Hopfield and Erik Winfree
681
Synchronization of neural networks by mutual learning and its application to cryptography
Einat Klein, Rachel Mislovaty, Ido Kanter, Andreas Ruttor and Wolfgang Kinzel
689
Nearly Tight Bounds for the Continuum-Armed Bandit Problem
Robert D. Kleinberg
697
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
Vladimir Koltchinski, Manel Martinez-Ramon and Stefan Posse
705
Newscast EM
Wojtek Kowalczyk and Nikos Vlassis
713
On Semi-Supervised Classification
Balaji Krishnapuram, David Williams, Ya Xue, Alexander Hartemink, Lawrence Carin and Mario Figueiredo
721
An Application of Boosting to Graph Classification
Taku Kudo, Eisaku Maeda and Yuji Matsumoto
729
Methods Towards Invasive Human Brain Computer Interfaces
Thomas Navin Lal, Thilo Hinterberger, Guido Widman, Michael Schroder, N. Jeremy Hill, Wolfgang Rosenstiel, Christian E. Elger, Bernhard Schölkopf and Niels Birbaumer
737
Beat Tracking the Graphical Model Way
Dustin Lang and Nando de Freitas
745
Semi-supervised Learning via Gaussian Processes
Neil D. Lawrence and Michael I. Jordan
753
Joint MRI Bias Removal Using Entropy Minimization Across Images
Erik G. Learned-Miller and Parvez Ahammad
761
Rate- and Phase-coded Autoassociative Memory
Máté Lengyel and Peter Dayan
769
Maximum Likelihood Estimation of Intrinsic Dimension
Elizaveta Levina and Peter J. Bickel
777
Planning for Markov Decision Processes with Sparse Stochasticity
Maxim Likhachev, Geoff Gordon and Sebastian Thrun
785
Incremental Learning for Visual Tracking
Jongwoo Lim, David A, Ross, Ruei-Sung Lin and Ming-Hsuan Yang
793
Adaptive Discriminative Generative Model and Its Applications
Ruei-Sung Lin, David A, Ross, Jongwoo Lim and Ming-Hsuan Yang
801
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
Yuanqing Lin and Daniel D. Lee
809
Multiple Alignment of Continuous Time Series
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis and Andrew Emili
817
An Investigation of Practical Approximate Nearest Neighbor Algorithms
Ting Liu, Andrew W. Moore, Alexander Gray and Ke Yang
825
Mistake Bounds for Maximum Entropy Discrimination
Philip M. Long and Xinyu Wu
833
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Le Lu, Gregory D. Hager and Laurent Younes
841
Semi-supervised Learning with Penalized Probabilistic Clustering
Zhengdong Lu and Todd K. Leen
849
Limits of Spectral Clustering
Ulrike de Luxburg, Olivier Bousquet and Mikhail Belkin
857
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits
Wolfgang Maass, Robert A. Legenstein and Nils Bertschinger
865
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms
Omid Madani, David M. Pennock and Gary William Flake
873
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
Mario Marchand and Mohak Shah
881
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
Tim K. Marks, John Hershey, J. Cooper Roddey and Javier R. Movellan
889
Linear Multilayer Independent Component Analysis for Large Natural Scenes
Yoshitatsu Matsuda and Kazunori Yamaguchi
897
Conditional Models of Identity Uncertainty with Application to Noun Coreference
Andrew McCallum and Ben Wellner
905
Multiple Relational Embedding
Roland Memisevic and Geoffrey Hinton
913
Kernels for Multi--task Learning
Charles A. Micchelli and Massimiliano Pontil
921
A Topographic Support Vector Machine: Classification Using Local Label Configurations
Johannes Mohr and Klaus Obermayer
929
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity
Marcelo A. Montemurro and Stefano Panzeri
937
Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks
Joris M. Mooij and Hilbert J. Kappen

商品描述(中文翻譯)

描述:
年度神經信息處理系統(NIPS)會議是神經計算的旗艦會議。它吸引了一個多樣化的參與者群體,包括物理學家、神經科學家、數學家、統計學家和計算機科學家。演講內容跨學科,涉及算法、學習理論、認知科學、神經科學、腦部成像、視覺、語音和信號處理、強化學習和控制、新興技術和應用等領域。只有百分之二十五的論文提交被接受在NIPS上發表,因此其質量非常高。本卷收錄了2004年12月在溫哥華舉行的會議上發表的論文。

勞倫斯·K·索爾(Lawrence K. Saul)是賓夕法尼亞大學計算機和信息科學系的助理教授,也是2004年NIPS會議的主席。

亞伊爾·韋斯(Yair Weiss)是耶路撒冷希伯來大學計算機科學與工程學院的高級講師,也是2004年NIPS會議的程序主席。

萊昂·博圖(Léon Bottou)是新澤西州普林斯頓NEC實驗室的高級研究科學家,也是2004年NIPS會議的出版主席。

目錄:
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捐贈者
NIPS基金會
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