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

Front Cover
Lawrence K. Saul, Yair Weiss, Léon Bottou
MIT Press, 2005 - Computers - 1668 pages
Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.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.
 

Contents

A Large Deviation Bound for the Area Under the ROC Curve
9
Harmonising Chorales by Probabilistic Inference MORAY ALLAN
25
A Direct Formulation for Sparse PCA Using Semidefinite
41
An application to object
57
Computing regularization paths for learning multiple kernels
73
Breaking SVM Complexity with CrossTraining GÖKHAN
81
LargeScale Prediction of Disulphide Bond Connectivity PIERRE
97
Bayesian Clustering of NonStationary Data
105
Semisupervised Learning with Penalized Probabilistic Clustering
849
Methods for Estimating the Computational Power
865
PACBayes Learning of Conjunctions and Classification
881
Linear Multilayer Independent Component Analysis for Large
897
Multiple Relational Embedding ROLAND MEMISEVIC and GEOFFREY
913
Classification
929
Validity Estimates for Loopy Belief Propagation on Binary
945
Optimal subgraphical models MUKUND NARASIMHAN and JEFF
961

Maximising Sensitivity in a Spiking Network ANTHONY J BELL
121
Whos In the Picture TAMARA L BERG ALEXANDER C BERG
137
A Second Order Cone programming Formulation for Classifying
153
Responding to Modalities with Different Latencies FREDRIK
169
Hierarchical Distributed Representations for Statistical Language
185
A Computational Theory
201
Dependent Gaussian Processes PHILLIP BOYLE and MARCUS FREAN
217
Incremental Algorithms for Hierarchical Classification NICOLÒ
233
SubMicrowatt Analog VLSI Support Vector Machine for Pattern
249
Using Machine Learning to Break Visual Human Interaction
265
Modeling Conversational Dynamics as a MixedMemory Markov
281
Distributed Information Regularization on Graphs ADRIAN
297
A Latent
313
Semigroup Kernels on Finite Sets MARCO CUTURI
329
SelfBounded Learning
345
Triangle Fixing Algorithms for the Metric Nearness Problem
361
Sparse Coding of Natural Images Using an Overcomplete Set
377
Seeing through water ALEXEI EFROS University of Oxford VOLKAN
393
ExplorationExploitation Tradeoffs for Experts Algorithms
409
Learning HyperFeatures for Visual Identification ANDRAS
425
OnChip Compensation of DeviceMismatch Effects in Analog
441
A Hidden Markov Model for de Novo Peptide Sequencing BERND
457
Joint Probabilistic Curve Clustering and Alignment SCOTT
473
InstanceBased Relevance Feedback for Image Retrieval GIORGIO
489
Hierarchical Clustering of a Mixture Model JACOB GOLDBERGER
505
The Cascade SVM HANS
521
Integrating Topics and Syntax THOMAS L GRIFFITHS Massachusetts
537
characteristic propagation
553
An Auditory Paradigm for BrainComputer Interfaces N JEREMY
569
HOFSTOETTER MANUEL GIL KYNAN ENG GIACOMO INDIVERI
577
Unsupervised Variational Bayesian Learning of Nonlinear Models
593
Message Errors in Belief Propagation ALEXANDER T IHLER JOHN
609
A Cost Function for Clustering
625
Online Bounds for Bayesian Algorithms SHAM M KAKADE
641
Generalization Error and Algorithmic Convergence of Median
657
Face Detection Efficient and Rank Deficient WOLF KIENZLE
673
Synchronization of neural networks by mutual learning and
689
Optimal Aggregation of Classifiers and Boosting Maps
705
On SemiSupervised Classification BALAJI KRISHNAPURAM
721
Methods Towards Invasive Human Brain Computer Interfaces
737
Semisupervised Learning via Gaussian Processes NEIL D
753
Rate and Phasecoded Autoassociative Memory MÁTÉ LENGYEL
769
Planning for Markov Decision Processes with Sparse Stochasticity
785
Adaptive Discriminative Generative Model and Its Applications
801
Multiple Alignment of Continuous Time Series JENNIFER
817
Mistake Bounds for Maximum Entropy Discrimination PHILIP M
833
Stable adaptive control with online learning ANDREW Y
977
A Harmonic Excitation StateSpace Approach to Blind Separation
993
Discrete profile alignment via constrained information bottleneck
1009
Logconcavity Results on Gaussian Process Methods
1025
Modeling Nonlinear Dependencies in Natural Images using
1041
Efficient OutofSample Extension of DominantSet Clusters
1057
Active Learning for Anomaly and RareCategory Detection
1073
New Criteria and a New Algorithm for Learning in MultiAgent
1089
Chemosensory Processing in a Spiking Model of the Olfactory
1105
An Information Maximization Model of Eye Movements LAURA
1121
Coarticulation in Markov Decision Processes KHASHAYAR
1137
Following Curved Regularized Optimization Solution Paths
1153
Outlier Detection with Oneclass Kernel Fisher Discriminants
1169
SemiMarkov Conditional Random Fields for Information
1185
Edge of Chaos Computation in MixedMode VLSI A Hard
1201
Assignment of Multiplicative Mixtures in Natural Images ODELIA
1217
RealTime Pitch Determination of One or More Voices
1233
Resolving Perceptual Aliasing In The Presence Of Noisy Sensors
1249
Dynamic Bayesian Networks for BrainComputer Interfaces
1265
Intrinsically Motivated Reinforcement Learning SATINDER SINGH
1281
Learning Syntactic Patterns for Automatic Hypernym Discovery
1297
Using the Equivalent Kernel to Understand Gaussian Process
1313
MaximumMargin Matrix Factorization NATHAN SREBRO University
1329
Fast Rates to Bayes for Kernel Machines INGO STEINWART
1345
Modelling Uncertainty in the Game of Go DAVID H STERN
1353
Distributed Occlusion Reasoning for Tracking with Nonparametric
1369
Hierarchical Dirichlet
1385
Contextual Models for Object Detection Using Boosted Random
1401
Synergies between Intrinsic and Synaptic Plasticity in Individual
1417
Supervised Graph Inference JEANPHILIPPE VERT Ecole des Mines
1433
InstanceSpecific Bayesian Model Averaging for Classification
1449
Identifying ProteinProtein Interaction Sites on a GenomeWide
1465
Exponential Family Harmoniums with an Application
1481
The Variational Ising Classifier VIC Algorithm for Coherently
1497
lonorm Minimization for Basis Selection DAVID P WIPF
1513
Efficient Kernel Discriminant Analysis via QR Decomposition
1529
Using Random Forests in the Structured Language Model PENG
1545
Efficient Kernel Machines Using the Improved Fast Gauss
1561
Inference Attention and Decision in a Bayesian Neural
1577
The Convergence of Contrastive Divergences ALAN YUILLE UCLA
1593
Probabilistic Computation in Spiking Populations RICHARD
1609
Classsize Independent Generalization Analsysis of Some
1625
Nonparametric Transforms of Graph Kernels for SemiSupervised
1641
Subject Index
1657
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About the author (2005)

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. Lé on Bottou is a Research Scientist at NEC Labs America.

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