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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 30000010127679 | QA76.87 A38 2005 | Open Access Book | Proceedings, Conference, Workshop etc. | Searching... |
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Summary
Summary
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.
Author Notes
Léon Bottou is a Research Scientist at NEC Labs America.
Table of Contents
Contents | p. v |
Preface | p. xix |
Donors | p. xxi |
NIPS foundation | p. xxii |
Committees | p. xxiii |
Reviewers | p. xxiv |
Learning first-order Markov models for control | p. 1 |
A Large Deviation Bound for the Area Under the ROC Curve | p. 9 |
Learning Preferences for Multiclass Problems | p. 17 |
Harmonising Chorales by Probabilistic Inference | p. 25 |
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces | p. 33 |
A Direct Formulation for Sparse PCA Using Semidefinite Programming | p. 41 |
Comparing Beliefs, Surveys, and Random Walks | p. 49 |
The power of feature clustering: An application to object detection | p. 57 |
Blind One-microphone Speech Separation: A Spectral Learning Approach | p. 65 |
Computing regularization paths for learning multiple kernels | p. 73 |
Breaking SVM Complexity with Cross-Training | p. 81 |
Co-Training and Expansion: Towards Bridging Theory and Practice | p. 89 |
Large-Scale Prediction of Disulphide Bond Connectivity | p. 97 |
Spike Sorting: Bayesian Clustering of Non-Stationary Data | p. 105 |
Exponentiated Gradient Algorithms for Large-margin Structured Classification | p. 113 |
Maximising Sensitivity in a Spiking Network | p. 121 |
Non-Local Manifold Tangent Learning | p. 129 |
Who's in the Picture | p. 137 |
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks | p. 145 |
A Second Order Cone programming Formulation for Classifying Missing Data | p. 153 |
Support Vector Classification with Input Data Uncertainty | p. 161 |
Responding to Modalities with Different Latencies | p. 169 |
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis | p. 177 |
Hierarchical Distributed Representations for Statistical Language Modeling | p. 185 |
Markov Networks for Detecting Overlapping Elements in Sequence Data | p. 193 |
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity | p. 201 |
Convergence and No-Regret in Multiagent Learning | p. 209 |
Dependent Gaussian Processes | p. 217 |
Proximity Graphs for Clustering and Manifold Learning | p. 225 |
Incremental Algorithms for Hierarchical Classifications | p. 233 |
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms | p. 241 |
Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation | p. 249 |
A Machine Learning Approach to Conjoint Analysis | p. 257 |
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) | p. 265 |
Hierarchical Eigensolver for Transition Matrices in Spectral Methods | p. 273 |
Modeling Conversational Dynamics as a Mixed-Memory Markov Process | p. 281 |
Theories of Access Consciousness | p. 289 |
Distributed Information Regularization on Graphs | p. 297 |
Confidence Intervals for the Area Under the ROC Curve | p. 305 |
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account | p. 313 |
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM | p. 321 |
Semigroup Kernals on Finite Sets | p. 329 |
Analysis of a greedy active learning strategy | p. 337 |
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees | p. 345 |
Bayesian inference in spiking neurons | p. 353 |
Triangle Fixing Algorithms for the Metric Nearness Problem | p. 361 |
Pictorial Structures for Molecular Modeling: Interpreting Density Maps | p. 369 |
Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units | p. 377 |
Making Latin Manuscripts Searchable using gHMM's | p. 385 |
Seeing through Water | p. 393 |
Experts in a Markov Decision Process | p. 401 |
Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments | p. 409 |
A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees | p. 417 |
Learning Hyper-Features for Visual Identification | p. 425 |
Sampling Methods for Unsupervised Learning | p. 433 |
On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks | p. 441 |
Object Classification from a Single Example Utilizing Class Relevance Metrics | p. 449 |
A Hidden Markov Model for de Novo Peptide Sequencing | p. 457 |
Implicit Wiener Series for Higher-Order Image Analysis | p. 465 |
Joint Probabilistic Curve Clustering and Alignment | p. 473 |
Discriminant Saliency for Visual Recognition from Cluttered Scenes | p. 481 |
Instance-Based Relevance Feedback for Image Retrieval | p. 489 |
Euclidean Embedding of Co-Occurrence Data | p. 497 |
Hierarchical Clustering of a Mixture Model | p. 505 |
Neighbourhood Components Analysis | p. 513 |
Parallel Support Vector Machines: The Cascade SVM | p. 521 |
Semi-Supervised Learning by Entropy Minimization | p. 529 |
Integrating Topics and Syntax | p. 537 |
Result Analysis of the NIPS 2003 Feature Selection Challenge | p. 545 |
Theory of localized synfire chain: characteristic propagation speed of stable spike pattern | p. 553 |
The Entire Regulation Path for the Support Vector Machine | p. 561 |
An Auditory Paradigm for Brain-Computer Interfaces | p. 569 |
The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning | p. 577 |
Schema Learning: Experience-Based Construction of Predictive Action Models | p. 585 |
Unsupervised Variational Bayesian Learning of Nonlinear Models | p. 593 |
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill | p. 601 |
Message Errors in Belief Propagation | p. 609 |
Parametric Embedding for Class Visualization | p. 617 |
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernal Feature Space | p. 625 |
Economic Properties of Social Networks | p. 633 |
Online Bounds for Bayesian Algorithms | p. 641 |
Maximal Margin Labeling for Multi-Topic Text Categorization | p. 649 |
Generalization Error and Algorithmic Convergence of Median Boosting | p. 657 |
Boosting on Manifolds: Adaptive Regularization of Base Classifiers | p. 665 |
Face Detection -- Efficient and Rank Deficient | p. 673 |
Neural Networks Computation by In Vitro Transcriptional Circuits | p. 681 |
Synchronization of neural networks by mutual learning and its application to cryptography | p. 689 |
Nearly Tight Bounds for the Continuum-Armed Bandit Problem | p. 697 |
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging | p. 705 |
Newscast EM | p. 713 |
On Semi-Supervised Classification | p. 721 |
An Application of Boosting to Graph Classification | p. 729 |
Methods Towards Invasive Human Brain Computer Interfaces | p. 737 |
Beat Tracking the Graphical Model Way | p. 745 |
Semi-supervised Learning via Gaussian Processes | p. 753 |
Joint MRI Bias Removal Using Entropy Minimization Across Images | p. 761 |
Rate- and Phase-coded Autoassociative Memory | p. 769 |
Maximum Likelihood Estimation of Intrinsic Dimension | p. 777 |
Planning for Markov Decision Processes with Sparse Stochasticity | p. 785 |
Incremental Learning for Visual Tracking | p. 793 |
Adaptive Discriminative Generative Model and Its Applications | p. 801 |
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation | p. 809 |
Multiple Alignment of Continuous Time Series | p. 817 |
An Investigation of Practical Approximate Nearest Neighbor Algorithms | p. 825 |
Mistake Bounds for Maximum Entropy Discrimination | p. 833 |
A Three Tiered Approach for Articulated Object Action Modeling and Recognition | p. 841 |
Semi-supervised Learning with Penalized Probabilistic Clustering | p. 849 |
Limits of Spectral Clustering | p. 857 |
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits | p. 865 |
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms | p. 873 |
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data | p. 881 |
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters | p. 889 |
Linear Multilayer Independent Component Analysis for Large Natural Scenes | p. 897 |
Conditional Models of Identity Uncertainty with Application to Noun Coreference | p. 905 |
Multiple Relational Embedding | p. 913 |
Kernels for Multi--task Learning | p. 921 |
A Topographic Support Vector Machine: Classification Using Local Label Configurations | p. 929 |
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity | p. 937 |
Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks | p. 945 |
Common-Frame Model for Object Recognition | p. 953 |
Optimal sub-graphical models | p. 961 |
Detecting Significant Multidimensional Spatial Clusters | p. 969 |
Stable adaptive control with online learning | p. 977 |
Mass Meta-analysis in Talairach Space | p. 985 |
A Harmonic Excitation State-Space Approach to Blind Separation of Speech | p. 993 |
Expectation Consistent Free Energies for Approximate Inference | p. 1001 |
Discrete profile alignment via constrained information bottleneck | p. 1009 |
Synergistic Face Detection and Pose Estimation with Energy-Based Models | p. 1017 |
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning | p. 1025 |
Variational Minimax Estimation of Discrete Distributions under KL Loss | p. 1033 |
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution | p. 1041 |
Approximately Efficient Online Mechanism Design | p. 1049 |
Efficient Out-of-Sample Extension of Dominant-Set Clusters | p. 1057 |
A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound | p. 1065 |
Active Learning for Anomaly and Rare-Category Detection | p. 1073 |
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs | p. 1081 |
New Criteria and a New Algorithm for Learning in Multi-Agent Systems | p. 1089 |
Conditional Random Fields for Object Recognition | p. 1097 |
Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition | p. 1105 |
Hierarchical Bayesian Inference in Networks of Spiking Neurons | p. 1113 |
An Information Maximization Model of Eye Movements | p. 1121 |
Brain Inspired Reinforcement Learning | p. 1129 |
Coarticulation in Markov Decision Processes | p. 1137 |
Learning, Regularization and Ill-Posed Inverse Problems | p. 1145 |
Following Curved Regularized Optimization Solution Paths | p. 1153 |
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning | p. 1161 |
Outlier Detection with One-class Kernel Fisher Discriminants | p. 1169 |
Semi-parametric Exponential Family PCA | p. 1177 |
Semi-Markov Conditional Random Fields for Information Extraction | p. 1185 |
Kernel Methods for Implicit Surface Modeling | p. 1193 |
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid | p. 1201 |
Learning Gaussian Process Kernels via Hierarchical Bayes | p. 1209 |
Assignment of Multiplicative Mixtures in Natural Images | p. 1217 |
On the Adaptive Properties of Decision Trees | p. 1225 |
Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization | p. 1233 |
Probabilistic Inference of Alternative Splicing Events in Microarray Data | p. 1241 |
Resolving Perceptual Aliasing In The Presence Of Noisy Sensors | p. 1249 |
Algebraic Set Kernels with Application to Inference Over Local Image Representations | p. 1257 |
Dynamic Bayesian Networks for Brain-Computer Interfaces | p. 1265 |
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities | p. 1273 |
Intrinsically Motivated Reinforcement Learning | p. 1281 |
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters | p. 1289 |
Learning Syntactic Patterns for Automatic Hypernym Discovery | p. 1297 |
Surface Reconstruction using Learned Shape Models | p. 1305 |
Using the Equivalent Kernel to Understand Gaussian Process Regression | p. 1313 |
Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices | p. 1321 |
Maximum-Margin Matrix Factorization | p. 1329 |
Density Level Detection is Classification | p. 1337 |
Fast Rates to Bayes for Kernel Machines | p. 1345 |
Modelling Uncertainty in the Game of Go | p. 1353 |
Constraining a Bayesian Model of Human Visual Speed Perception | p. 1361 |
Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation | p. 1369 |
Temporal-Difference Networks | p. 1377 |
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes | p. 1385 |
Heuristics for Ordering Cue Search in Decision Making | p. 1393 |
Contextual Models for Object Detection Using Boosted Random Fields | p. 1401 |
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model | p. 1409 |
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons | p. 1417 |
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection | p. 1425 |
Supervised Graph Inference | p. 1433 |
Binet-Cauchy Kernels | p. 1441 |
Instance-Specific Bayesian Model Averaging for Classification | p. 1449 |
Saliency-Driven Image Acuity Modulation on a Reconfigurable Array of Spiking Silicon Neurons | p. 1457 |
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale | p. 1465 |
Adaptive Manifold Learning | p. 1473 |
Exponential Family Harmoniums with an Application to Information Retrieval | p. 1481 |
Machine Learning Applied to Perception: Decision Images for Gender Classification | p. 1489 |
The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data | p. 1497 |
Generative Affine Localisation and Tracking | p. 1505 |
L_0-norm Minimization for Basis Selection | p. 1513 |
Multi-agent Cooperation in Diverse Population Games | p. 1521 |
Efficient Kernel Discriminant Analysis via QR Decomposition | p. 1529 |
Maximum Margin Clustering | p. 1537 |
Using Random Forests in the Structured Language Model | p. 1545 |
Solitaire: Man Versus Machine | p. 1553 |
Efficient Kernel Machines Using the Improved Fast Gauss Transform | p. 1561 |
Two-Dimensional Linear Discriminant Analysis | p. 1569 |
Inference, Attention, and Decision in a Bayesian Neural Architecture | p. 1577 |
The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters | p. 1585 |
The Convergence of Contrastive Divergences | p. 1593 |
Self-Tuning Spectral Clustering | p. 1601 |
Probabilistic Computation in Spiking Populations | p. 1609 |
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection | p. 1617 |
Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification | p. 1625 |
Semi-supervised Learning on Directed Graphs | p. 1633 |
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning | p. 1641 |
Kernel Projection Machine: a New Tool for Pattern Recognition | p. 1649 |
Subject Index | p. 1657 |
Author Index | p. 1664 |