Article

On the sample complexity of pac-learning using random and chosen examples

Authors:

Bonnie Eisenberg and

Ronald L. RivestAuthors Info & Claims

COLT '90: Proceedings of the third annual workshop on Computational learning theory

July 1990

Pages 154 - 162

Published: 01 July 1990 Publication History

Abstract

No abstract available.

Cited By

View all

Bordes AErtekin SWeston JBottou L(2005)Fast Kernel Classifiers with Online and Active LearningThe Journal of Machine Learning Research10.5555/1046920.11948986(1579-1619)Online publication date: 1-Dec-2005
https://dl.acm.org/doi/10.5555/1046920.1194898
Hasenjäger MRitter H(2002)Active learning in neural networksNew learning paradigms in soft computing10.5555/505831.505836(137-169)Online publication date: 1-Jan-2002
https://dl.acm.org/doi/10.5555/505831.505836
Gentile CHelmbold DBartlett PMansour Y(1998)Improved lower bounds for learning from noisy examplesProceedings of the eleventh annual conference on Computational learning theory10.1145/279943.279965(104-115)Online publication date: 24-Jul-1998
https://dl.acm.org/doi/10.1145/279943.279965
Show More Cited By

Index Terms

On the sample complexity of pac-learning using random and chosen examples
1. Computing methodologies
  1. Machine learning
2. Theory of computation
  1. Models of computation
    1. Probabilistic computation

Recommendations

Sample size lower bounds in PAC learning by algorithmic complexity theory
Read More
Computational Sample Complexity

In a variety of PAC learning models, a trade-off between time and information seems to exist: with unlimited time, a small amount of information suffices, but with time restrictions, more information sometimes seems to be required. In addition, it has ...
Read More
Sample complexity of hidden subgroup problem
Abstract
The hidden subgroup problem (HSP) has been attracting much attention in quantum computing, since several well-known quantum algorithms including Shor's algorithm can be described in a uniform framework as quantum methods to address ...
Highlights
- The upper and lower bounds for sample complexity of the hidden subgroup problem.
Read More

Comments

Information & Contributors

Information

Published In

COLT '90: Proceedings of the third annual workshop on Computational learning theory

July 1990

395 pages

ISBN:1558601465

Editors:
Mark Fulk
Univ. of Rochester, Rochester, NY
,
John Case
State Univ. of New York, Buffalo, NY

Publisher

Morgan Kaufmann Publishers Inc.

San Francisco, CA, United States

Publication History

Published: 01 July 1990

Check for updates

Qualifiers

Article

Conference

COLT90

Sponsor:

COLT90: 3rd Annual Workshop on Computational Learning Theory

August 6 - 8, 1990

New York, Rochester, USA

Acceptance Rates

Overall Acceptance Rate 35 of 71 submissions, 49%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Other Metrics

View Author Metrics

Citations

Cited By

View all

Bordes AErtekin SWeston JBottou L(2005)Fast Kernel Classifiers with Online and Active LearningThe Journal of Machine Learning Research10.5555/1046920.11948986(1579-1619)Online publication date: 1-Dec-2005
https://dl.acm.org/doi/10.5555/1046920.1194898
Hasenjäger MRitter H(2002)Active learning in neural networksNew learning paradigms in soft computing10.5555/505831.505836(137-169)Online publication date: 1-Jan-2002
https://dl.acm.org/doi/10.5555/505831.505836
Gentile CHelmbold DBartlett PMansour Y(1998)Improved lower bounds for learning from noisy examplesProceedings of the eleventh annual conference on Computational learning theory10.1145/279943.279965(104-115)Online publication date: 24-Jul-1998
https://dl.acm.org/doi/10.1145/279943.279965
Freund YSeung HShamir ETishby N(1997)Selective Sampling Using the Query by Committee AlgorithmMachine Language10.1023/A:100733050853428:2-3(133-168)Online publication date: 1-Sep-1997
https://dl.acm.org/doi/10.1023/A%3A1007330508534
Auer PLong PLeighton FGoodrich M(1994)Simulating access to hidden information while learningProceedings of the twenty-sixth annual ACM symposium on Theory of Computing10.1145/195058.195152(263-272)Online publication date: 23-May-1994
https://dl.acm.org/doi/10.1145/195058.195152
Turán G(1993)Lower bounds for PAC learning with queriesProceedings of the sixth annual conference on Computational learning theory10.1145/168304.168382(384-391)Online publication date: 1-Aug-1993
https://dl.acm.org/doi/10.1145/168304.168382

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Sample size lower bounds in PAC learning by algorithmic complexity theory

Computational Sample Complexity

Sample complexity of hidden subgroup problem

Comments

Published In

Sponsors

Publisher

Publication History

Check for updates

Qualifiers

Conference

Acceptance Rates

Other Metrics

Article Metrics

Other Metrics

Cited By

Login options

Full Access

Abstract

Cited By

Index Terms

Recommendations

Sample size lower bounds in PAC learning by algorithmic complexity theory

Computational Sample Complexity

Sample complexity of hidden subgroup problem

Comments

Information

Published In

Sponsors

Publisher

Publication History

Check for updates

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Get Access

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations