|
|
|
|
| LEADER |
00000cam a2200000Ia 4500 |
| 001 |
SCIDIR_ocn681311176 |
| 003 |
OCoLC |
| 005 |
20231117044519.0 |
| 006 |
m o d |
| 007 |
cr cnu---unuuu |
| 008 |
101113s1990 caua ob 101 0 eng d |
| 010 |
|
|
|z 90041088
|
| 040 |
|
|
|a OCLCE
|b eng
|e pn
|c OCLCE
|d OCLCQ
|d OPELS
|d OCLCO
|d OCLCQ
|d OCLCF
|d OCLCQ
|d E7B
|d OCLCQ
|d UIU
|d N$T
|d YDXCP
|d OCL
|d OCLCQ
|d VT2
|d WYU
|d HS0
|d LEAUB
|d UHL
|d SFB
|d LIP
|d OCLCQ
|d OCLCO
|d UAB
|d S2H
|d OCLCO
|d COM
|d OCLCO
|d OCLCQ
|d OCLCO
|
| 019 |
|
|
|a 755054338
|a 1048152580
|a 1064081973
|a 1086418912
|a 1112980051
|a 1117506279
|a 1120893037
|a 1181908927
|a 1227636450
|a 1269193159
|a 1277204367
|a 1281717923
|
| 020 |
|
|
|a 9780323137706
|q (electronic bk.)
|
| 020 |
|
|
|a 0323137709
|q (electronic bk.)
|
| 020 |
|
|
|a 1299196551
|
| 020 |
|
|
|a 9781299196551
|
| 020 |
|
|
|z 1558601465
|
| 020 |
|
|
|z 9781558601468
|
| 035 |
|
|
|a (OCoLC)681311176
|z (OCoLC)755054338
|z (OCoLC)1048152580
|z (OCoLC)1064081973
|z (OCoLC)1086418912
|z (OCoLC)1112980051
|z (OCoLC)1117506279
|z (OCoLC)1120893037
|z (OCoLC)1181908927
|z (OCoLC)1227636450
|z (OCoLC)1269193159
|z (OCoLC)1277204367
|z (OCoLC)1281717923
|
| 042 |
|
|
|a dlr
|
| 050 |
|
4 |
|a Q325.5
|b .W67 1990eb
|
| 072 |
|
7 |
|a MAT
|x 000000
|2 bisacsh
|
| 082 |
0 |
4 |
|a 511.3
|2 23
|
| 111 |
2 |
|
|a Workshop on Computational Learning Theory
|n (3rd :
|d 1990 :
|c Rochester, N.Y.)
|
| 245 |
1 |
0 |
|a Proceedings of the Third Annual Workshop on Computational Learning Theory :
|b University of Rochester, Rochester, New York, August 6-8, 1990 /
|c sponsored by the ACM SIGACT/SIGART ; [edited by] Mark Fulk, John Case.
|
| 260 |
|
|
|a San Mateo, Calif. :
|b Morgan Kaufmann Publishers,
|c �1990.
|
| 300 |
|
|
|a 1 online resource :
|b illustrations
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 504 |
|
|
|a Includes bibliographical references and index.
|
| 538 |
|
|
|a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
|u http://purl.oclc.org/DLF/benchrepro0212
|5 MiAaHDL
|
| 583 |
1 |
|
|a digitized
|c 2010
|h HathiTrust Digital Library
|l committed to preserve
|2 pda
|5 MiAaHDL
|
| 588 |
0 |
|
|a Print version record.
|
| 505 |
8 |
|
|a 2 Stochastic Rules and Their Hierarchical Parameter Structures3 A Learning Criterion for Stochastic Rules -- A Stochastic PAC Model; 4 Hierarchical Learning Based on the MDL Principle; 5 The Optimality of MDL Rules and Their Convergence Rates; 6 Sample Complexity and Learnability of Stochastic Decision List Classes; 7 Concluding Remarks; References; Chapter 6. ON THE COMPLEXITY OF LEARNING MINIMUM TIME-BOUNDED TURING MACHINES; Abstract; 1. INTRODUCTION; 2. DEFINITIONS; 3. MAIN RESULTS; 4. PROOFS; 5. OPEN QUESTIONS; References; Chapter 7. INDUCTIVE INFERENCE FROM POSITIVE DATA IS POWERFUL
|
| 505 |
8 |
|
|a ABSTRACTINTRODUCTION; PRELIMINARIES; ELEMENTARY FORMAL SYSTEMS; INDUCTIVE INFERENCE FROM POSITIVE DATA; INDUCTIVE INFERENCE OF EFS MODELS FROM POSITIVE DATA; INDUCTIVE INFERENCE OF EFS LANGUAGES FROM POSITIVE DATA; DISCUSSION; Acknowledgments; References; Chapter 8. INDUCTIVE IDENTIFICATION OF PATTERN LANGUAGES WITH RESTRICTED SUBSTITUTIONS; ABSTRACT; PATTERN LANGUAGES OVER AN ARBITRARY BASE; PUMPING LEMMA; APPLICATION TO INDUCTIVE INFERENCE; References; Chapter 9. Pattern Languages Are Not Learnable; 1 Introduction; 2 PRELIMINAR IES; 3 The Main Result; Acknowledgments; References
|
| 506 |
|
|
|3 Use copy
|f Restrictions unspecified.
|2 star
|5 MiAaHDL
|
| 533 |
|
|
|a Electronic reproduction.
|b [Place of publication not identified] :
|c HathiTrust Digital Library,
|d 2010.
|5 MiAaHDL
|
| 546 |
|
|
|a English.
|
| 650 |
|
0 |
|a Computational learning theory
|v Congresses.
|
| 650 |
|
6 |
|a Th�eorie de l'apprentissage informatique
|0 (CaQQLa)201-0265184
|v Congr�es.
|0 (CaQQLa)201-0378219
|
| 650 |
|
7 |
|a MATHEMATICS
|x General.
|2 bisacsh
|
| 650 |
|
7 |
|a Computational learning theory
|2 fast
|0 (OCoLC)fst00871997
|
| 650 |
|
7 |
|a Apprentissage automatique
|x Congr�es.
|2 ram
|
| 655 |
|
2 |
|a Congress
|0 (DNLM)D016423
|
| 655 |
|
7 |
|a proceedings (reports)
|2 aat
|0 (CStmoGRI)aatgf300027316
|
| 655 |
|
7 |
|a Conference papers and proceedings
|2 fast
|0 (OCoLC)fst01423772
|
| 655 |
|
7 |
|a Conference papers and proceedings.
|2 lcgft
|
| 655 |
|
7 |
|a Actes de congr�es.
|2 rvmgf
|0 (CaQQLa)RVMGF-000001049
|
| 700 |
1 |
|
|a Fulk, Mark A.
|
| 700 |
1 |
|
|a Case, John,
|d 1942-
|
| 710 |
2 |
|
|a ACM Special Interest Group for Automata and Computability Theory.
|
| 710 |
2 |
|
|a SIGART.
|
| 740 |
0 |
|
|a Colt '90.
|
| 740 |
0 |
|
|a Computational learning theory.
|
| 776 |
0 |
8 |
|i Print version:
|a Workshop on Computational Learning Theory (3rd : 1990 : Rochester, N.Y.).
|t Proceedings of the Third Annual Workshop on Computational Learning Theory.
|d San Mateo, Calif. : Morgan Kaufmann Publishers, �1990
|z 9781558601468
|w (DLC) 90041088
|w (OCoLC)21972833
|
| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9781558601468
|z Texto completo
|
