Advances in Neural Information Processing Systems 17 : Proceedings of the 2004 Conference (Hardcover) (神經資訊處理系統進展 17:2004年會議論文集 (精裝版))
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 折 $1,764
- 語言: 英文
- 頁數: 1696
- 裝訂: Hardcover
- ISBN: 0262195348
- ISBN-13: 9780262195348
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相關分類:
人工智慧、Machine Learning
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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. Ng1 A Large Deviation Bound for the Area Under the ROC Curve
Shivani Agarwal, Thore Graepel, Ralf Herbrich and Dan Roth9 Learning Preferences for Multiclass Problems
Fabio Aiolli and Alessandro Sperduti17 Harmonising Chorales by Probabilistic Inference
Moray Allan and Christopher K. I. Williams25 The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung Pang, Daphne Koller, Sebastian Thrun and James Davis33 A Direct Formulation for Sparse PCA Using Semidefinite Programming
Alexandre d'Aspremont, Laurent El Ghaoui, Michael I. Jordan and Gert R. G. Lanckriet41 Comparing Beliefs, Surveys, and Random Walks
Erik Aurell, Uri Gordon and Scott Kirkpatrick49 The power of feature clustering: An application to object detection
Shai Avidan and Moshe Butman57 Blind One-microphone Speech Separation: A Spectral Learning Approach
Francis R. Bach and Michael I. Jordan65 Computing regularization paths for learning multiple kernels
Francis R. Bach, Romain Thibaux and Michael I. Jordan73 Breaking SVM Complexity with Cross-Training
Gökhan H. Bakir, Léon Bottou and Jason Weston81 Co-Training and Expansion: Towards Bridging Theory and Practice
Maria-Florina Balcan, Avrim Blum and Ke Yang89 Large-Scale Prediction of Disulphide Bond Connectivity
Pierre Baldi, Jianlin Cheng and Alessandro Vullo97 Spike Sorting: Bayesian Clustering of Non-Stationary Data
Aharon Bar-Hillel, Adam Spiro and Eran Stark105 Exponentiated Gradient Algorithms for Large-margin Structured Classification
Peter L. Bartlett, Michael Collins, Benjamin Taskar and David A. McAllester113 Maximising Sensitivity in a Spiking Network
Anthony J. Bell and Lucas Parra121 Non-Local Manifold Tangent Learning
Yoshua Bengio and Martin Monperrus129 Who's in the Picture
Tamara L. Berg, Alexander C. Berg, Jaety Edwards and David Forsyth137 At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks
Nils Bertschinger, Thomas Natschläger and Robert A. Legenstein145 A Second Order Cone programming Formulation for Classifying Missing Data
Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy and Alex Smola153 Support Vector Classification with Input Data Uncertainty
Jinbo Bi and Tong Zhang161 Responding to Modalities with Different Latencies
Fredrik Bissmarck, Hiroyuki Nakahara, Kenji Doya and Okihide Hikosaka169 Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
Tobias Blaschke and Laurenz Wiskott177 Hierarchical Distributed Representations for Statistical Language Modeling
John Blitzer, Kilian Weinberger, Lawrence Saul and Fernando C. N. Pereira185 Markov Networks for Detecting Overlapping Elements in Sequence Data
Joseph Bockhorst and Mark Craven193 Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity
Sander. M. Bohte and Michael C Mozer201 Convergence and No-Regret in Multiagent Learning
Michael Bowling209 Dependent Gaussian Processes
Phillip Boyle and Marcus Frean217 Proximity Graphs for Clustering and Manifold Learning
Miguel A. Carreira-Perpinan and Richard S. Zemel225 Incremental Algorithms for Hierarchical Classifications
Nicolò Cesa-Bianchi, Claudio Gentile, Andrea Tironi and Luca Zaniboni233 Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
Nicolò Cesa-Bianchi, Claudio Gentile and Luca Zaniboni241 Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation
Shantanu Chakrabartty and Gert Cauwenberghs249 A Machine Learning Approach to Conjoint Analysis
Olivier Chapelle and Zaid Harchaoui257 Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
Kumar Chellapilla and Patrice Y. Simard265 Hierarchical Eigensolver for Transition Matrices in Spectral Methods
Chakra Chennubhotla and Allan Jepson273 Modeling Conversational Dynamics as a Mixed-Memory Markov Process
Tanzeem Choudhury and Sumit Basu281 Theories of Access Consciousness
Michael D. Colagrosso and Michael C Mozer289 Distributed Information Regularization on Graphs
Adrian Corduneanu and Tommi S. Jaakkola297 Confidence Intervals for the Area Under the ROC Curve
Corinna Cortes and Mehryar Mohri305 Similarity and Discrimination in Classical Conditioning: A Latent Variable Account
Aaron C. Courville, Nathaniel D. Daw and David S. Touretzky313 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 Sañudo321 Semigroup Kernals on Finite Sets
Marco Cuturi and Jean-Philippe Vert329 Analysis of a greedy active learning strategy
Sanjoy Dasgupta337 The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees
Ofer Dekel, Shai Shalev-Shwartz and Yoram Singer345 Bayesian inference in spiking neurons
Sophie Deneve353 Triangle Fixing Algorithms for the Metric Nearness Problem
Inderjit S. Dhillon, Suvrit Sra and Joel Tropp361 Pictorial Structures for Molecular Modeling: Interpreting Density Maps
Frank DiMaio, Jude Shavlik and George Phillips369 Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units
Eizaburo Doi and Michael S. Lewicki377 Making Latin Manuscripts Searchable using gHMM's
Jaety Edwards, Yee Whye Teh, David Forsyth, Roger Bock, Michael Maire and Grace Vesom385 Seeing through Water
Alexei Efros, Volkan Isler, Jianbo Shi and Mirkó Visontai393 Experts in a Markov Decision Process
Eyal Even-Dar, Sham Kakade and Yishay Mansour401 Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments
Daniela Pucci de Farias and Nimrod Megiddo409 A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees
Daniela Pucci de Farias and Benjamin Van Roy417 Learning Hyper-Features for Visual Identification
Andras D. Ferencz, Erik G. Learned-Miller and Jitendra Malik425 Sampling Methods for Unsupervised Learning
Rob Fergus, Andrew Zisserman and Pietro Perona433 On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks
Miguel Figueroa, Seth Bridges and Chris Diorio441 Object Classification from a Single Example Utilizing Class Relevance Metrics
Michael Fink449 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 Widmayer457 Implicit Wiener Series for Higher-Order Image Analysis
Matthias O. Franz and Bernhard Schölkopf465 Joint Probabilistic Curve Clustering and Alignment
Scott J. Gaffney and Padhraic Smyth473 Discriminant Saliency for Visual Recognition from Cluttered Scenes
Dashan Gao and Nuno Vasconcelos481 Instance-Based Relevance Feedback for Image Retrieval
Giorgio Giacinto and Fabio Roli489 Euclidean Embedding of Co-Occurrence Data
Amir Globerson, Gal Chechik, Fernando C. N. Pereira and Naftali Tishby497 Hierarchical Clustering of a Mixture Model
Jacob Goldberger and Sam T. Roweis505 Neighbourhood Components Analysis
Jacob Goldberger, Sam T. Roweis, Geoffrey Hinton and Ruslan Salakhutdinov513 Parallel Support Vector Machines: The Cascade SVM
Hans Peter Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic and Vladimir Vapnik521 Semi-Supervised Learning by Entropy Minimization
Yves Grandvalet and Yoshua Bengio529 Integrating Topics and Syntax
Thomas L. Griffiths, Mark Steyvers, David M. Blei and Joshua B. Tenenbaum537 Result Analysis of the NIPS 2003 Feature Selection Challenge
Isabelle Guyon, Steve Gunn, Asa Ben-Hur and Gideon Dror545 Theory of localized synfire chain: characteristic propagation speed of stable spike pattern
Kosuke Hamaguchi, Masato Okada and Kazuyuki Aihara553 The Entire Regulation Path for the Support Vector Machine
Trevor Hastie, Saharon Rosset, Robert Tibshirani and Ji Zhu561 An Auditory Paradigm for Brain-Computer Interfaces
N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Niels Birbaumer and Bernhard Schölkopf569 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 Verschure577 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 Valpola593 A Generalized Bradley-Terry Model: From Group Competition to Individual Skill
Tzu-Kuo Huang, Chih-Jen Lin and Ruby C. Weng601 Message Errors in Belief Propagation
Alexander T. Ihler, John W. Fisher and Alan S. Willsky609 Parametric Embedding for Class Visualization
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths and Joshua B. Tenenbaum617 The Laplacian PDF Distance: A Cost Function for Clustering in a Kernal Feature Space
Robert Jenssen, Deniz Erdogmus, José C. Príncipe and Torbjørn Eltoft625 Economic Properties of Social Networks
Sham Kakade, Michael Kearns, Luis Ortiz, Robin Pemantle and Siddharth Suri633 Online Bounds for Bayesian Algorithms
Sham Kakade and Andrew Y. Ng641 Maximal Margin Labeling for Multi-Topic Text Categorization
Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira and Eisaku Maeda649 Generalization Error and Algorithmic Convergence of Median Boosting
Balázs Kégl657 Boosting on Manifolds: Adaptive Regularization of Base Classifiers
Balázs Kégl and Ligen Wang665 Face Detection -- Efficient and Rank Deficient
Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz and Bernhard Schölkopf673 Neural Networks Computation by In Vitro Transcriptional Circuits
Jongmin Kim, John Hopfield and Erik Winfree681 Synchronization of neural networks by mutual learning and its application to cryptography
Einat Klein, Rachel Mislovaty, Ido Kanter, Andreas Ruttor and Wolfgang Kinzel689 Nearly Tight Bounds for the Continuum-Armed Bandit Problem
Robert D. Kleinberg697 Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
Vladimir Koltchinski, Manel Martinez-Ramon and Stefan Posse705 Newscast EM
Wojtek Kowalczyk and Nikos Vlassis713 On Semi-Supervised Classification
Balaji Krishnapuram, David Williams, Ya Xue, Alexander Hartemink, Lawrence Carin and Mario Figueiredo721 An Application of Boosting to Graph Classification
Taku Kudo, Eisaku Maeda and Yuji Matsumoto729 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 Birbaumer737 Beat Tracking the Graphical Model Way
Dustin Lang and Nando de Freitas745 Semi-supervised Learning via Gaussian Processes
Neil D. Lawrence and Michael I. Jordan753 Joint MRI Bias Removal Using Entropy Minimization Across Images
Erik G. Learned-Miller and Parvez Ahammad761 Rate- and Phase-coded Autoassociative Memory
Máté Lengyel and Peter Dayan769 Maximum Likelihood Estimation of Intrinsic Dimension
Elizaveta Levina and Peter J. Bickel777 Planning for Markov Decision Processes with Sparse Stochasticity
Maxim Likhachev, Geoff Gordon and Sebastian Thrun785 Incremental Learning for Visual Tracking
Jongwoo Lim, David A, Ross, Ruei-Sung Lin and Ming-Hsuan Yang793 Adaptive Discriminative Generative Model and Its Applications
Ruei-Sung Lin, David A, Ross, Jongwoo Lim and Ming-Hsuan Yang801 Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
Yuanqing Lin and Daniel D. Lee809 Multiple Alignment of Continuous Time Series
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis and Andrew Emili817 An Investigation of Practical Approximate Nearest Neighbor Algorithms
Ting Liu, Andrew W. Moore, Alexander Gray and Ke Yang825 Mistake Bounds for Maximum Entropy Discrimination
Philip M. Long and Xinyu Wu833 A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Le Lu, Gregory D. Hager and Laurent Younes841 Semi-supervised Learning with Penalized Probabilistic Clustering
Zhengdong Lu and Todd K. Leen849 Limits of Spectral Clustering
Ulrike de Luxburg, Olivier Bousquet and Mikhail Belkin857 Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits
Wolfgang Maass, Robert A. Legenstein and Nils Bertschinger865 Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms
Omid Madani, David M. Pennock and Gary William Flake873 PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
Mario Marchand and Mohak Shah881 Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
Tim K. Marks, John Hershey, J. Cooper Roddey and Javier R. Movellan889 Linear Multilayer Independent Component Analysis for Large Natural Scenes
Yoshitatsu Matsuda and Kazunori Yamaguchi897 Conditional Models of Identity Uncertainty with Application to Noun Coreference
Andrew McCallum and Ben Wellner905 Multiple Relational Embedding
Roland Memisevic and Geoffrey Hinton913 Kernels for Multi--task Learning
Charles A. Micchelli and Massimiliano Pontil921 A Topographic Support Vector Machine: Classification Using Local Label Configurations
Johannes Mohr and Klaus Obermayer929 Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity
Marcelo A. Montemurro and Stefano Panzeri937 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。
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