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Advances in Neural Information Processing Systems 10: Proceedings of the 1997 Conference

Advances in Neural Information Processing Systems 10: Proceedings of the 1997 Conference

by Michael I. Jordan, Michael J. Kearns, Sara A. Solla

ISBN-10: 0262100762

ISBN-13: 9780262100762

Pub. Date: 06/05/1998

Publisher: MIT Press

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented


The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Product Details

MIT Press
Publication date:
Bradford Books Series
Product dimensions:
7.30(w) x 10.10(h) x 2.30(d)
Age Range:
18 Years

Table of Contents

NIPS Committees
Part I Cognitive Science
Synchronized Auditory and Cognitive 40 Hz Attentional Streams, and the Impact of Rhythmic Expectation on Auditory Scene Analysis
On Parallel Versus Serial Processing: A Computational Study of Visual Search
Task and Spatial Frequency Effects on Face Specialization
Neural Basis of Object-Centered Representations
A Neural Network Model of Naive Preference and Filial Imprinting in the Domestic Chick
Adaptation in Speech Motor Control
Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report
Multi-modular Associative Memory
Serial Order in Reading Aloud: Connectionist Models and Neighborhood Structure
A Superadditive-Impairment Theory of Optic Aphasia
A Hippocampal Model of Recognition Memory
Correlates of Attention in a Model of Dynamic Visual Recognition
Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting
Comparison of Human and Machine Word Recognition
Part II Neuroscience
Coding of Naturalistic Stimuli by Auditory Midbrain Neurons
Refractoriness and Neural Precision
Statistical Models of Conditioning
Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse Correlation
Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordins
Instabilities in Eye Movement Control: A Model of Periodic Alternating Nystagmus
Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning
Gradients for Retinotectal Mapping
A Mathematical Model of Axon Guidance by Diffusible Factors
Computing with Action Potentials (Invited Talk)
A Model of Early VisualProcessing
Perturbative M-sequences for Auditory Systems Identification
Effects of Spike Timing underlying Binocular Integration and Rivalry in a Neural Model of Early Visual Cortex
Dynamic Stochastic Synapses as Computational Units
Synaptic Transmission: An Information-Theoretic Perspective
Toward a Single-cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites
Just One View: Invariances in Inferotemporal Cell Tuning
On the Separation of Signals from Neighboring Cells in Tetrode Recordings
Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings
Modeling Complex Cells in an Awake Macaque during Natural Image Viewing
Part III Theory
The Canonical Distortion Measure in Feature Space and 1-NN Classification
Multiple Threshold Neural Logic
Generalization In Decision Trees and DNF: Does Size Matter?
Selecting Weighting Factors in Logarithmic Opinion Pools
New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit
Boltzmann Machine Learning Using Mean Field Theory and Linear Response Correction
Relative Loss Bounds for Multidimensional Regression Problems
Asymptotic Theory for Regularization: One-dimensional Linear Case
Two Approaches to Optimal Annealing
Structural Risk Minimization for Nonparametric Time Series Prediction
Analytical Study of the Interplay Between Architecture and Predictability
Globally Optimal On-line Learning Rules
Minimax and Hamiltonian Dynamics of Excitatory-inhibitory Networks
Data-dependent Structural Risk Minimization for Perceptron Decision Trees
From Regularization Operators to Support Vector Kernels
The Rectified Gaussian Distribution
On-line Learning from Finite Training Sets in Nonlinear Networks
Competitive On-line Linear Regression
On the Infeasibility of Training Neural Networks with Small Squared Errors
The Storage Capacity of a Fully-Connected Committee Machine
The Efficiency and the Robustness of Natural Gradient Descent Learning Rule
Part IV Algorithms and Architecture
Ensemble Learning for Multi-layer Networks
Radial Basis Functions: A Bayesian Treatment
Shared Context Probabilistic Transducers
Approximating Posterior Distributions in Belief Networks Using Mixture
Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning Rules
An Annealed Self-organizing Map for Source Channel Coding
Incorporating Test Inputs into Learning
On Efficient Heuristic Ranking of Hypotheses
Learning to Order Things
Regularisation in Sequential Learning Algorithms
Agnostic Classification of Markovian Sequences
Ensemble and Modular Approaches for Face Detection: A Comparison
A Revolution: Belief Propagation in Graphs with Cycles
Hierarchical Non-linear Factor Analysis and Topographic Maps
Regression with Input-Dependent Noise: A Gaussian Process Treatment
Linear Concepts and Hidden Variables: An Empirical Study
Classification by Pairwise Coupling
Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis
Nonlinear Markov Networks for Continuous Variables
Active Data Clustering
Function Approximation with the Sweeping Hinge Algorithm
The Error Coding and Substitution PaCTs
S-Map: A Network with a Simple Self-Organization Algorithm for Generative Topographic Mappings
Learning Nonlinear Overcomplete Representations for Efficient Coding
Factorizing Multivariate Function Classes
A Framework for Multiple-Instance Learning
An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures
Estimating Dependency Structure as a Hidden Variable
Combining Classifiers Using Correspondence Analysis
Learning Path Distributions Using Nonequilibrium Diffusion Networks
Learning Generative Models with the Up-Propagation Algorithm
An Incremental Nearest Neighbor Algorithm with Queries
RCC Cannot Compute Certain FSA, Even with Arbitrary Transfer Functions
EM Algorithms for PCA and SPCA
Local Dimensionality Reduction
Prior Knowledge in Support Vector Kernels
Training Methods for Adaptive Boosting of Neural Networks
Learning Continuous Attractors in Recurrent Networks
Monotonic Networks
Stacked Density Estimation
Bidirectional Retrieval from Associative Memory
Mapping a Manifold of Perceptual Observations
Graph Matching with Hierarchical Discrete Relaxation
Multiplicative Updating Rule for Blind Separation Derived from the Method of Scoring
Part V Implementation
A 1,000-neuron System with One Million 7-bit Physical Interconnections
Silicon Retina with Adaptive Filtering Properties
Analog VLSI Model of Intersegmental Coordination with Nearest-Neighbor Coupling
An Analog VLSI Neural Network for Phase-based Machine Vision
Part VI Speech, Handwriting and Signal Processing
Analysis of Drifting Dynamics With neural Network Hidden Markov Models
Bayesian Robustification for Audio Visual Fusion
Modeling Acoustic Correlations by Factor Analysis
Blind Separation of Radio Signals in Fading Channels
Hybrid NN/HMM-based Speech Recognition with a Discriminant Neural Feature Extraction
Part VII Visual Processing
A Non-parametric Multi-scale Statistical Model for Natural Images
Recovering Perspective Pose with a Dual Step EM Algorithm
Bayesian Model of Surface Perception
Features as Sufficient Statistics
Detection of First and Second Order Motion
A Simple and Fast Neural Network Approach to Stereovision
Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework
Visual Navigation in a Robot Using Zig-Zag Behavior
2D Observers for Human 3D Object Recognition?
Self-similarity Properties of Natural Images
Multiresolution Tangent Distance for Affine-invariant Classification
Phase Transitions and the Perceptual Organization of Video Sequences
Part VIII Applications
Using Expectation to Guide Processing: A Study of Three Real-world Applications
Structure Driven Image Database Retrieval
A General Purpose Image Processing Chip: Orientation Detection
An Analog VLSI Model of the Fly Elementary Motion Detector
Melonet I: Neural Nets for Inventing Baroque-style Chorale Variations
Extended ICA Removes Artifacts From Electroencephalographic Recordings
A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure
A Neural Network Based Head Tracking System
Wavelet Models for Video Time-series
Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks
Learning to Schedule Straight-Line Code
Enhancing Q-learning for Optimal Asset Allocation
Intrusion Detection with Neural Networks
Incorporating Contextual Information in White Blood Cell Identification
Bach in a Box -- Real-time Harmony
Experiences with Bayesian Learning in a Real World Application
A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction
Use of a Multi-layer Perceptron to Predict Malignancy in Ovarian Tumors
Modelling Seasonality and Trends in Daily Rainfall Data
The Observer-Observation Dilemma in Neuro-Forecasting
Part IX Control, Navigation and Planning
Generalized Prioritized Sweeping
Nonparametric Model-Based Reinforcement Learning
An Improved Policy Iteration Algorithm for Partially Observable Mdps
Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments
Reinforcement Learning for Continuous Stochastic Control Problems
Adaptive Choice of Grid and Time in Reinforcement Learning
Reinforcement Learning with Hierarchies of Machines
Multi-time Models for Temporally Abstract Planning
How to Dynamically Merge Markov Decision Processes
The Asymptotic Convergence-Rate of Q-learning
Hybrid Reinforcement Learning and Its Application to Biped Robot Control
Index of Authors
Keyword Index

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