Advances in Neural Information Processing Systems 14: Proceedings of the 2001 Conference

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Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani
MIT Press, 2002 - Information storage and retrieval systems - 1594 pages
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Contents

Modeling Temporal Structure in Classical Conditioning
3
Motivated Reinforcement Learning
11
Human Data and a Model
19
Fragment Completion in Humans and Machines
27
Natural Language Grammar Induction using a ConstituentContext Model
35
The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay
43
A Rational Analysis of Cognitive Control in a Speeded Discrimination Task
51
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing
59
Novel Iteration Schemes for the Cluster Variation Method
415
Efficiency versus Convergence of Boolean Kernels for OnLine Learning Algorithms
423
SmallWorld Phenomena and the Dynamics of Information
431
Kernel Machines and Boolean Functions
439
Boosting and Maximum Likelihood for Exponential Models
447
Means Correlations and Bounds
455
A Variational Approach to Learning Curves
463
Entropy and Inference Revisited
471

Grammar Transfer in a Second Order Recurrent Neural Network
67
Generalizable Relational Binding from Coarsecoded Distributed Representations
75
Generalization and Binding
83
Grammatical Bigrams
91
Causal Categorization with Bayes Nets
99
Constructing Distributed Representations using Additive Clustering
107
Reinforcement Learning and Time Perceptiona Model of Animal Experiments
115
A Quantitative Model of Counterfactual Reasoning
123
Bayesian Morphometry of Hippocampal Cells Suggests SameCell Somatodendritic Repulsion
133
Modularity in the Motor System Decomposition of Muscle Patterns as Combinations of TimeVarying Synergies
141
Receptive Field Structure of Flow Detectors for Heading Perception
149
Towards Brain Computer Interfacing
157
Orientational and Geometric Determinants of Place and Headdirection
165
Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway
173
A MaximumLikelihood Approach to Modeling Multisensory Enhancement
181
ACh Uncertainty and Cortical Inference
189
Learning in an Unlearnable Force Field
197
Exact Differential Equation Population Dynamics for IntegrateandFire Neurons
205
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex
213
A Theory of Neural Integration in the HeadDirection System
221
3 State Neurons for Contextual Processing
229
Associative Memory in Realistic Neuronal Networks
237
Selfregulation Mechanism of Temporally Asymmetric Hebbian Plasticity
245
InformationGeometric Decomposition in Spike Analysis
253
Eye Movements and the Maturation of Cortical Orientation Selectivity
261
Characterizing Neural Gain Control using Spiketriggered Covariance
269
Correlation Codes in Neuronal Populations
277
Why Neuronal Dynamics should Control Synaptic Learning Rules
285
Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes
293
Activity Driven Adaptive Stochastic Resonance
301
Spike Timing and the Coding of Naturalistic Sounds in a Central Auditory Area of Song Birds
309
Neural Implementation of Bayesian Inference in Population Codes
317
Generating Velocity Tuning by Asymmetric Recurrent Connections
325
Sampling Techniques for Kernel Methods
335
Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons
343
The Noisy Euclidean Traveling Salesman Problem and Learning
351
On the Generalization Ability of OnLine Learning Algorithms
359
On KernelTarget Alignment
367
PAC Generalization Bounds for Cotraining
375
Analysis of Sparse Bayesian Learning
383
Algorithmic Luckiness
391
Distribution of Mutual Information
399
Information Geometrical Framework for Analyzing Belief Propagation Decoder
407
Asymptotic Universality for Learning Curves of Support Vector Machines
479
On the Convergence of Leveraging
487
Scaling Laws and Local Minima in Hebbian ICA
495
Computing Time Lower Bounds for Recurrent Sigmoidal Neural Networks
503
On the Concentration of Spectral Properties
511
Gaussian Process Regression with Mismatched Models
519
InformationGeometrical Significance of Sparsity in Gallager Codes
527
Fast Parameter Estimation Using Greens Functions
535
Generalization Performance of Some Learning Problems in Hilbert Functional Spaces
543
SemiSupervised MarginBoost
553
RaoBlackwellised Particle Filtering via Data Augmentation
561
Thin Junction Trees
569
The Infinite Hidden Markov Model
577
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
585
Duality Geometry and Support Vector Regression
593
Latent Dirichlet Allocation
601
Incorporating Invariances in NonLinear Support Vector Machines
609
A Generalization of Principal Component Analysis to the Exponential Family
617
Convolution Kernels for Natural Language
625
A Parallel Mixture of SVMs for Very Large Scale Problems
633
Pranking with Ranking
641
Spectral Kernel Methods for Clustering
649
TAP Gibbs Free Energy Belief Propagation and Sparsity
657
Adaptive Nearest Neighbor Classification using Support Vector Machines
665
Learning from Infinite Data in Finite Time
673
A Kernel Method for MultiLabelled Classification
681
Approximate Dynamic Programming via Linear Programming
689
Adaptive Sparseness Using Jeffreys Prior
697
Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM
705
Adaptive Particle Filters
713
Fast LargeScale TransformationInvariant Clustering
721
Learning to Model Observations as Products of Hidden Variables
729
Very Loopy Probability Propagation for Unwrapping Phase Images
737
Discriminative Direction for Kernel Classifiers
745
Escaping the Convex Hull with Extrapolated Vector Machines
753
Kernel Feature Spaces and Nonlinear Blind Source Separation
761
The Method of Quantum Clustering
769
Active Information Retrieval
777
Online Learning with Kernels
785
A Dynamic HMM for Online Segmentation of Sequential Data
793
Minimax Probability Machine
801
Index of Authors
809
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