Towards a DNA Sequencing Theory (Learning a String) (Preliminary Version)
作者： Ming Li
DOI:
关键词:
摘要:
参考文章(13)
Arthur M. Lesk, Computational Molecular Biology: Sources and Methods for Sequence Analysis ,(1989)
Michael J. Kearns, Computational Complexity of Machine Learning ,(1990)
Ming Li, Paul M.B. Vitanyi, A Theory of Learning Simple Concepts Under Simple Distributions conference on learning theory. pp. 386- ,(1989) , 10.1016/B978-0-08-094829-4.50033-7
James A. Storer, Data compression: methods and theory Computer Science Press, Inc.. ,(1987)
David Haussler, Quantifying inductive bias: AI learning algorithms and Valiant's learning framework Artificial Intelligence. ,vol. 36, pp. 177- 221 ,(1988) , 10.1016/0004-3702(88)90002-1
W. Maass, G. Turan, On the complexity of learning from counterexamples foundations of computer science. pp. 262- 267 ,(1989) , 10.1109/SFCS.1989.63488
Peter Friedland, Laurence H. Kedes, Discovering the secrets of DNA Communications of The ACM. ,vol. 28, pp. 1164- 1186 ,(1985) , 10.1145/4547.4550
John Gallant, David Maier, James Astorer, On finding minimal length superstrings Journal of Computer and System Sciences. ,vol. 20, pp. 50- 58 ,(1980) , 10.1016/0022-0000(80)90004-5
B. K. Natarajan, On learning Boolean functions symposium on the theory of computing. pp. 296- 304 ,(1987) , 10.1145/28395.28427
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth, Occam's razor Information Processing Letters. ,vol. 24, pp. 377- 380 ,(1987) , 10.1016/0020-0190(87)90114-1