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

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： 內容 前言 捐贈者 NIPS基金會 委員會 評審人員 類似商品 $1,800 Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference (Hardcover) VIP 95折 $3,430 $3,259 Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference (Hardcover) VIP 95折 $870 $827 Semi-Supervised Learning(Hardcover) VIP 95折 $3,240 $3,078 Data-Driven Computational Neuroscience: Machine Learning and Statistical Models VIP 95折 $2,030 $1,929 An Introductory Course in Computational Neuroscience (Computational Neuroscience Series) $1,575 $1,544 Dataset Shift in Machine Learning (Hardcover) VIP 95折 $4,820 $4,579 Applied Machine Learning $1,150 $1,127 Bioinformatics Technologies VIP 95折 $3,410 $3,240 Applied Machine Learning $1,450 $1,421 Stochastic Methods in Neuroscience (Hardcover)