COLT '91 - 1st Edition - ISBN: 9781558602137, 9781483299143

COLT '91

1st Edition

Proceedings of the Fourth Annual Workshop, UC Santa Cruz, California, August 5-7, 1991

Editors: COLT
eBook ISBN: 9781483299143
Imprint: Morgan Kaufmann
Published Date: 1st July 1991
Page Count: 371
Sales tax will be calculated at check-out Price includes VAT/GST
54.95
43.99
72.95
Unavailable
Price includes VAT/GST
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

COLT '91: Proceedings of the Fourth Annual Workshop on Computational Learning Theory covers the papers presented at the Fourth Workshop on Computational Learning Theory, held at the University of California at Santa Cruz on August 5-7, 1991. The book focuses on quantitative theories of machine learning.

The selection first offers information on the role of learning in autonomous robots; tracking drifting concepts using random examples; investigating the distribution assumptions in the PAC learning model; and simultaneous learning of concepts and simultaneous estimation of probabilities.The text then examines the calculation of the learning curve of Bayes optimal classification algorithm for learning a perceptron with noise and a geometric approach to threshold circuit complexity.

The manuscript takes a look at learning curves in large neural networks, learnability of infinitary regular sets, and learning monotone DNF with an incomplete membership oracle. Topics include monotone DNF learning algorithm, difficulties in learning infinitary regular sets, learning of a perception rule, and annealed approximation. The book also examines the fast identification of geometric objects with membership queries and a loss bound model for on-line stochastic prediction strategies.

The selection is a valuable source of information for researchers interested in the computational learning theory.

Table of Contents


Foreword


Invited Talks


Learning and Generalization


The Role of Learning in Autonomous Robots


Session 1: Morning, Aug 5


Tracking Drifting Concepts Using Random Examples


Investigating the Distribution Assumptions in the Pac Learning Model


Simultaneous Learning of Concepts and Simultaneous Estimation of Probabilities


Learning by Smoothing: A Morphological Approach


Session 2:


Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension


Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron with Noise


Probably Almost Bayes Decisions


Session 3: Afternoon, Aug 5


Invited Talk


Learning and Generalization


Session 4:


A Geometric Approach to Threshold Circuit Complexity


Learning Curves in Large Neural Networks


On the Learnability of Infinitary Regular Sets


Session 5: Morning, Aug 6


Learning Monotone DNF with an Incomplete Membership Oracle


Redundant Noisy Attributes, Attribute Errors, and Linear-Threshold Learning Using Winnow


Learning in the Presence of Finitely or Infinitely Many Irrelevant Attributes


On-Line Learning with an Oblivious Environment and the Power of Randomization


Session 6:


Learning Monotone kμ-DNF Formulas on Product Distributions


Learning Probabilistic Read-Once Formulas on Product Distributions


Learning 2μ-DNF Formulas and kμ Decision Trees


Session 7: Afternoon, Aug 6


Invited Talk


The Role of Learning in Autonomous Robots


Session 8:


Polynomial-Time Learning of Very Simple Grammars from Positive Data


Relations Between Probabilistic and Team One-Shot Learners<

Details

No. of pages:
371
Language:
English
Copyright:
© Morgan Kaufmann 1991
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9781483299143

About the Editor

Ratings and Reviews