Proceedings of the Twelfth Annual Conference on Computational Learning Theory: July 6 - 9, 1999, Santa Cruz, California
Gespeichert in:
| Körperschaft: | |
|---|---|
| Format: | Tagungsbericht Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Assoc. for Computing Machinery
1999
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | V, 333 S. graph. Darst. |
| ISBN: | 1581131674 |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
Foreword
.....................................................................................................
vii
Tuesday, July
6,1999
Session
1
The Robustness of the p-norm Algorithms
......................................................................... 1
Claudio
Gentile, Nicholas Littlestone
Minimax Regret under Log Loss for General Classes of Experts,
.................................................... 12
Nicolo
Cesa-Bianchi,
Gábor Lugosi
On Prediction of Individual Sequences Relative to a set of Experts
.................................................. 19
Tsachy Weissman,
Neri
Merhav
Regret Bounds for Prediction Problems
.......................................................................... 29
Geoffrey J. Gordon
Session
2
On theory revision with queries
..................................................................................41
Robert H. Sloan,
György
Turan
Estimating a mixture of two product distributions
..................................................................53
Yoav
Freund, Yishay
Mansour
An Apprentice Learning Model
..................................................................................63
Stephen S.
Kwek
Session
3
Uniform-Distribution Attribute Noise Learnability
.................................................................75
Nader H. Bshouty, Jeffrey C. Jackson,
Christino
Tamon
On Learning in the Presence of Unspecified Attribute Values
....................................................... 81
Nader H. Bshouty, David K. Wilson
Learning Fixed-dimension Linear Thresholds From Fragmented Data
............................................... 88
Paul W. Goldberg
Wednesday, July
7,1999
Invited Talk
Approximation algorithms for clustering problems
............................................................... 100
David Shmoys
Session
4
An adaptive version of the boost-by-majority algorithm
........................................................... 102
Yoav
Freund
Drifting Games
............................................................................................... 114
Robert E. Schapire
Ш
Additive Models,
Boosting, and Inference for Generalized Divergences
.............................................
125
John Lafferty
134
Boosting as Entropy Projection
.................................................................................
J. KMnen, M. K. Warmuth
Multiclass Learning, Boosting, and Error-Correcting Codes
.......................................................
Venkatesan Guruswami,
Amit Sahai
Session
5
Theoretical Analysis of a Class of Randomized Regularization Methods
............................................
156
Tong
Zhang
PAC-Bayesian Model Averaging
...............................................................................
164
David McAllester
Viewing all Models as Probabilistic1
...........................................................................
171
Peter
Grunwald
Thursday, July
8,1999
Sessione
Reinforcement Learning and Mistake Bounded Algorithms
........................................................183
Yishay Mansour
Convergence analysis of temporal-difference learning algorithms
.................................................. 193
Vladislav
Tadić
Beating the Hold-Out
......................................................................................... 203
Avrim Blum, Adam Kalai, John
Langford
Microchoice Bounds and Self Bounding Learning Algorithms
.....................................................209
John Longford, Avrim Blum
Session
7
Learning Specialist Decision Lists
..............................................................................215
Atsuyoshi Nakamura
Linear Relations between Square-Loss and Kolmogorov Complexity
...............................................226
Yuri A. Kalnishkan
Individual sequence prediction- upper bounds and application for complexity
.......................................233
Chamy Allenberg
Sessione
Extensional Set Learning
........................................................... ....................243
S. A. Terwijn
On a generalized notion of mistake bounds
.................................. ................249
SanjayJain, Arun Sharma
On the intrinsic complexity of learning infinite objects from finite samples
..........................................257
E. Kinber,
С
Papazian,
С
Smith, R. Wiehagen
Friday, July
9,1999
Session
9
Covering Numbers for Support Vector Machines
.................................................................267
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert
С
Williamson
iv
Further Results on the Margin Distribution
...................................................................... 278
John Shawe-Taylor,
Nello Cristianini
Session
10
Attribute Efficient PAC-learning of DNF with Membership Queries
................................................ 286
Nader H. Bshouty, Jeffrey C. Jackson,
Christino
Tamon
On
PAC
Learning Using Winnow, Perceptron, and a Perceptron-Like Algorithm
.....................................296
Rocco
A. Servedio
Extension of the
PAC
Framework to Finite and Countable Markov Chains
.......................................... 308
David Gamarnik
Learning threshold functions with small weights using membership queries
......................................... 318
Elias
Abboud, Nader Agha, Nader H. Bshouty, Nizar Radwan, FathiSaleh
Exact learning of unordered tree patterns from queries
............................................................323
Thomas R. Amoth, Paul Cull,
Prasad
Tadepalli
Author Index
.................................................................................................333
|
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| illustrated | Illustrated |
| indexdate | 2024-07-09T18:38:19Z |
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| spelling | Conference on Computational Learning Theory 12 1999 Santa Cruz, Calif. Verfasser (DE-588)10013427-0 aut Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California New York, NY Assoc. for Computing Machinery 1999 V, 333 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Apprentissage automatique - Congrès ram algorithme apprentissage inriac apprentissage machine inriac complexité calcul inriac Computational learning theory Congresses Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 1999 Santa Cruz Calif. gnd-content Maschinelles Lernen (DE-588)4193754-5 s DE-604 Digitalisierung TU Muenchen application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008893496&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California Apprentissage automatique - Congrès ram algorithme apprentissage inriac apprentissage machine inriac complexité calcul inriac Computational learning theory Congresses Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)1071861417 |
| title | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_auth | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_exact_search | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_full | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_fullStr | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_full_unstemmed | Proceedings of the Twelfth Annual Conference on Computational Learning Theory July 6 - 9, 1999, Santa Cruz, California |
| title_short | Proceedings of the Twelfth Annual Conference on Computational Learning Theory |
| title_sort | proceedings of the twelfth annual conference on computational learning theory july 6 9 1999 santa cruz california |
| title_sub | July 6 - 9, 1999, Santa Cruz, California |
| topic | Apprentissage automatique - Congrès ram algorithme apprentissage inriac apprentissage machine inriac complexité calcul inriac Computational learning theory Congresses Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Apprentissage automatique - Congrès algorithme apprentissage apprentissage machine complexité calcul Computational learning theory Congresses Maschinelles Lernen Konferenzschrift 1999 Santa Cruz Calif. |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008893496&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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