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Abstract: Two protocols used for learning under the pac-learning model introduced by Valiant are learning from random examples and learning from membership queries. Membership queries have also been used to efficiently and exactly learn a concept class that is too difficult to pac-learn using random examples. We ask whether using membership queries-- in conjunction with or instead of random examples serve a new purpose: helping to reduce the total number of examples needed to pac-learn a concept class C... (Update)
Context of citations to this paper: More
...the other patterns, and still recover the same final hypothesis. Theoretical results and artificial examples discussed in Rivest and Eisenberg (1990) show that it is possible to invent malicious distributions for which the number of queries is comparable to the sample size,...
...problem. 3 Dense Learning Problems A learning problem is dense if every hypothesis has many hypotheses which are close but not equal to it [4]: Definition 1 A learning problem h Omega ; Hi is dense with respect to the probability measure D if for every h 2 H and every ffl 0...
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BibTeX entry: (Update)
B. Eisenberg. On the sample complexity of pac-learning using random and chosen examples. Master's thesis, Massachusetts Institute of Technology, 1991. http://citeseer.ist.psu.edu/eisenberg91sample.html More
@techreport{ eisenberg92sample,
author = "B. B. Eisenberg",
title = "{ON} {THE} {SAMPLE} {COMPLEXITY} {OF} {PAC}-{LEARNING} {USING} {RANDOM} {AND} {CHOSEN} {EXAMPLES}",
number = "MIT/LCS/TR-535",
pages = "38",
year = "1992",
url = "citeseer.ist.psu.edu/eisenberg91sample.html" }
Citations (may not include all citations):465 Learnability and the Vapnik-Chervonenkis dimension (context) - Blumer, Ehrenfeucht et al. - 1989 ACM DBLP
441 Queries and concept learning (context) - Angluin - 1988 ACM DBLP
348 Estimation of Dependences Based on Empirical Data (context) - Vapnik - 1982
244 Learning regular sets from queries and counterexamples (context) - Angluin - 1987 ACM DBLP
215 Learning decision lists - Rivest - 1987 ACM DBLP
184 Cryptographic limitations on learning boolean formulae and f.. - Kearns, Valiant - 1989
151 A gen- eral lower bound on the number of examples needed for.. (context) - Ehrenfeucht, Haussler et al. - 1989
144 Computational limitations on learning from ex- amples (context) - Pitt, Valiant - 1986
97 Learning read-once formulas with queries - Angluin, Hellerstein et al. - 1989 ACM DBLP
83 Geometrical and statistical properties of systems of linear .. (context) - Cover - 1965
48 Classifying learnable geometric concepts with the Vapnik-Che.. (context) - Blumer, Ehrenfeucht et al. - 1986 ACM
26 How fast can a threshold gate learn (context) - Maass, Tur
26 On learning a union of half spaces (context) - Baum - 1990 ACM
25 Dover Publications (context) - Coxeter - 1973
20 Probably approximately correct learning - Haussler - 1990 ACM DBLP
4 Types of queries for concept learning (context) - Angluin - 1986
3 Measurability constraints on pac learnability (context) - Ben-David, Benedek - 1991
1 Recent results in computational learning theory (context) - Pitt - 1990
1 A parametrization scheme for classifying models of learnabil.. (context) - Ben-David, Benedek et al. - 1989 ACM DBLP
1 Communications of the AUM (context) - Valiant, of et al. - 1984
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