Neural networks and efficient associative memory

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Neural networks and efficient associative memory

Full text

Pdf (1.61 MB)

Source

Annual Workshop on Computational Learning Theory archive
Proceedings of the eleventh annual conference on Computational learning theory table of contents

Madison, Wisconsin, United States

Pages: 235 - 246

Year of Publication: 1998

ISBN:1-58113-057-0

Authors

Matthias Miltrup	Fachbereich Informatik, Universität Frankfurt, Postfach 11 19 32, 60054 Frankfurt, Germany
Georg Schnitger	Fachbereich Informatik, Universität Frankfurt, Postfach 11 19 32, 60054 Frankfurt, Germany

Sponsors

University of Wisconsin : University of Wisconsin
UC @ Santa Cruz : UC @ Santa Cruz
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 1, Downloads (12 Months): 13, Citation Count: 0

Additional Information:

references index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/279943.279991 What is a DOI?

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.

	1	N. Alon, J. Spencer, P. ErdiSs. The Probabitistic Method, Wiley, 1992.
	2	E Frankl, Z. Filredi. A short proof of a theorem of Harper about Hamming spheres, Discrete Mathematics, 34, pp. 311-313, 1981.
	3	Yoav Freund, Boosting a weak learning algorithm by majority, Information and Computation, v.121 n.2, p.256-285, Sept. 1995 [doi>10.1006/inco.1995.1136]
	4	O. Goldreich , S. Goldwasser , D. Ron, Property testing and its connection to learning and approximation, Proceedings of the 37th Annual Symposium on Foundations of Computer Science, p.339, October 14-16, 1996
	5	Oded Goldreich , Dana Ron, Property testing in bounded degree graphs, Proceedings of the twenty-ninth annual ACM symposium on Theory of computing, p.406-415, May 04-06, 1997, El Paso, Texas, United States [doi>10.1145/258533.258627]
	6	J.J. Hopfield. Neural networks and physical systems with emergent collective computational abilities, Proc. of the National Academy of Sciences, 79, pp. 2554-2558, 1982.
	7	János Komlós , Ramamohan Paturi, Effect of connectivity in an associative memory model, Journal of Computer and System Sciences, v.47 n.2, p.350-373, Oct. 1993 [doi>10.1016/0022-0000(93)90036-V]
	8	Ilan Kremer , Noam Nisan , Dana Ron, On randomized one-round communication complexity, Proceedings of the twenty-seventh annual ACM symposium on Theory of computing, p.596-605, May 29-June 01, 1995, Las Vegas, Nevada, United States [doi>10.1145/225058.225277]
	9	M. Miltrup, G. Schnitger. Large deviation results for quadratic forms, Technical Report 2/98, Department of Computer Science, University of Frankfurt, 1998.
	10	M. Miltrup, G. Schnitger. Neural networks and efficient associative memory, Technical Report 3/98, Department of Computer Science, University of Frankfurt, 1998.