On optimal learning algorithms for multiplicity automata

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4005 LNAI, Issue , 2006, Pages 184-198

  Bisht, Laurence ^a   Bshouty, Nader H ^a   Mazzawi, Hanna ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; DIGITAL ARITHMETIC; MATRIX ALGEBRA; OPTIMAL SYSTEMS; POLYNOMIALS; QUERY LANGUAGES; THEOREM PROVING;

ARITHMETIC OPERATIONS; MULTIPLICITY AUTOMATA; OPTIMAL LEARNING ALGORITHMS;

LEARNING ALGORITHMS;

EID: 33746089159     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11776420_16     Document Type: Conference Paper

References (21)

1. D. Angluin. Learning regular sets from queries and counterexamples. Information and Computation, 75(2), 87-106, 1987.
2. D. Angluin. Queries and concept learning. Machine Learning, 2, 319-342, 1987.
3. M. Bläer. Lower bounds for the multiplicative complexity of atrix multiplication. Comput. Complexity, 8(3), 203-226, 1999.
4. A. Beimel, F. Bergadano, N. H. Bshouty, E. Kushilevitz, S. Varricchio. Learning functions represented as multiplicity automata. J. ACM, 47(3), 506-530, 2000.
5. F. Bergadano, N. H. Bshouty, C. Tamon, S. Varricchio. On Learning Programs and Small Depth Circuits. EuroCOLT. 150-161, 1997.
6. F. Bergadano, N. H. Bshouty, S. Varricchio. Learning Multivariate Polynomials from Substitution and Equivalence Queries, http://www.eccc.uni- trier.de/eccc, 1996.
7. F. Bergadano, D. Catalano, S. Varricchio. Learning Sat-k-DNF Formulas from Membership Queries-STOC 96, 126-130, 1996.
8. J. L. Balcáar, J. Díaz, R. Gavaldá O.Watanabe. A note on the query complexity of learning DFA. ALT 92. 53-62. 1992.
9. N. H. Bshouty, S. A. Goldman, T. R. Hancock, S. Matar. Asking Questions to Minimize Errors. J. Comput. Syst. Sci. 52(2), 268-286, 1996.
10. A. Beimel, E. Kushilevitz: Learning Boxes in High Dimension. Algorithmica, 22(1/2), 76-90, 1998.
11. N. H. Bshouty, C. Tamon, D. K. Wilson. Learning matrix functions over rings. Algorithmica 22(1/2), 91-111, 1998.
12. F. Bergadano, S. Varricchio. Learning Behaviors of Automata from Multiplicity and Equivalence Queries. SIAM J. Comput. 25(6), 1268-1280, 1996.
13. F. Bergadano and S. Varricchio. Learning behaviors of automata from shortest counterexamples. EuroCOLT 95, 380-391, 1996.
14. D. Coppersmith and S. Winograd. Matrix multiplication via arithmetic progressions. Journal of Symbolic Computation, 9, 251-280, 1990.
15. N. Elkies. On finite sequences satisfying linear recursions. Available at http://xxx.lanl.gov/abs/math.CO/0105007.
16. M. J. Kearns, L. G. Valiant. Cryptographic Limitations on Learning Boolean Formulae and Finite Automata. J. ACM, 41(1), 67-95, 1994.
17. N. Littlestone. Learning quickly when irrelevant attributes abound: A new linearthreshold algorithm. Machine Learning, 2, 285-318, 1987.
18. N. Littlestone and M. K. Warmuth. The weighted majority algorithm. Information and Computation, 108(2), 212-261, 1994.
19. W. Maass and G. Turán. Lower bound methods and seperation results for on-line learning models. Machine Learning, 9, 107-145, 1992.
20. H. Ohnishi, H. Seki, and T. Kasami. A polynomial time learning algorithm for recognizable series.IEICE Transactions on Information and Systems, E77-D(5), 1077-1085, 1994.
21. A. Shpilka. Lower Bounds for Matrix Product. SIAM J. Comput. 32(5), 1185-1200, 2003.