The Mathematics of Generalization: The Proceedings of the SFI - CNLS Workshop on Formal Approaches to Supervised Learning

The Mathematics of Generalization: The Proceedings of the SFI - CNLS Workshop on Formal Approaches to Supervised Learning

by David H. Wolpert
     
 

Contributions from workers in Bayesian analysis, machine learning, neural nets, PAC and VC theory, classical sampling theory statistics and the statistical physics of learning discuss the subjectSee more details below

Overview

Contributions from workers in Bayesian analysis, machine learning, neural nets, PAC and VC theory, classical sampling theory statistics and the statistical physics of learning discuss the subject

Product Details

ISBN-13:
9780201409833
Publisher:
Westview Press
Publication date:
01/28/1995
Series:
Santa Fe Institute Series, #20
Edition description:
REV
Pages:
460
Product dimensions:
1.02(w) x 6.00(h) x 9.00(d)

Table of Contents

Preface
The Status of Supervised Learning Science circa 1994 - The Search for a Consensus1
Reflections After Refereeing Papers for NIPS11
The Probably Approximately Correct (PAC) and Other Learning Models17
Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications37
The Relationship Between PAC, the Statistical Physics Framework, the Bayesian Framework, and the VC Framework117
Statistical Physics Models of Supervised Learning215
On Exhaustive Learning243
A Study of Maximal-Coverage Learning Algorithms279
On Bayesian Model Selection315
Soft Classification, a.k.a. Risk Estimation, via Penalized Log Likelihood and Smoothing Spline Analysis of Variance331
Current Research361
Preface to Simplifying Neural Networks by Soft Weight Sharing369
Simplifying Neural Networks by Soft Weight Sharing373
Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs395
Image Segmentation and Recognition409
Index435

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