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On-line learning of rectangles
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Source Annual Workshop on Computational Learning Theory archive
Proceedings of the fifth annual workshop on Computational learning theory table of contents
Pittsburgh, Pennsylvania, United States
Pages: 16 - 28  
Year of Publication: 1992
ISBN:0-89791-497-X
Authors
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 2,   Downloads (12 Months): 15,   Citation Count: 12
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ABSTRACT

This paper solves the following open problem: Is there an algorithm for on-line learning of rectangles i=1

    d
ai, ai+1,…,bi} over a discrete domain {1,…,n}d whose error bound is polylogarithmic in the size nd of the domain (i.e. polynomial in d and log n )? We give a positive solution by introducing a new design technique that appears to be of some interest on its own. The new learning algorithm for rectangles consists of 2d separate search strategies that search for the parameters a1,b1,…,ad,bd of the target rectangle. A learning algorithm with this type of modular design ends to fail because of the well known “credit assignment problem”: Which of the 2d local search strategies should be “blamed” when the global algorithm makes an error? We overcome this difficulty by employing local search strategies (“error tolerant binary search”) that are able to tolerate certain types of wrong credit assignments. Section 4 contains another application of this design technique: an algorithm for learning the union of two rectangles in the plane.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
A
 
H
D. Haussler, personal communication, 1989.
 
KMRSW
D.J. Kleitman, A.R. Meyer, R.L. Rivest, J. Spencer, K. Winklman, "Coping with errors in binary search procedures", J. Comp. Syst. Sci., 1980, 396 - 404.
 
L
 
MTa
W. Maass, G. Turin, "On the complexity of learning from counterexamples (extended abstract)", Proc of the 30th Annual LE.E.E. Symposium on Foundations of Computer Science, 1989, 262 - 267.
 
MTb
W. Maass, G. Turin, "Algorithms and Lower Bounds for On-line Learning of Geometrical Concepts", Report 316 (Oct. 1991), IIG-Report Series, Technische Universitaet Graz;, to appear in Machine Learning.
 
MTc
 
P
PV
 
SW
J. Spencer, P. Winkler, "Three thresholds for a liar", DIMACS Tech. Report 91 - 72 (Oct. 1991).
V

CITED BY  12
 

Collaborative Colleagues:
Zhixiang Chen: colleagues
Wolfgang Maass: colleagues

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