Proceedings of the tenth annual conference on Computational learning theory

COLT '97: Proceedings of the tenth annual conference on Computational learning theory

July 1997

1997 Proceeding

Chairmen:
Yoav Freund
AT&T Labs
,
Robert Schapire
AT&T Labs

Publisher:

Association for Computing Machinery
New York
NY
United States

Conference:

COLT97: Tenth Annual Conference on Computational Learning Theory Nashville Tennessee USA July 6 - 9, 1997

ISBN:

978-0-89791-891-6

Published:

01 July 1997

Sponsors:

SIGAI, AT&T Labs, SIGACT, Vanderbilt University

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Reflects downloads up to 25 Jan 2025Bibliometrics

Citation Count

461

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570

Downloads (12 months)

2,767

Downloads (cumulative)

14,438

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COLT '97: Proceedings of the tenth annual conference on Computational learning theory

1997

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A PAC analysis of a Bayesian estimator

John Shawe-Taylor,
Robert C. Williamson

Pages 2–9https://doi.org/10.1145/267460.267466

- 106
- 1,299
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Total Citations106
Total Downloads1,299
Last 12 Months355
Last 6 weeks40

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Learning logic programs by using the product homomorphism method

Tamás Horváth,
Robert H. Sloan,
György Turán

Pages 10–20https://doi.org/10.1145/267460.267468

- 7
- 280
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Total Citations7
Total Downloads280
Last 12 Months40
Last 6 weeks8

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On-line evaluation and prediction using linear functions

Philip M. Long

Pages 21–31https://doi.org/10.1145/267460.267471

- 4
- 183
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Total Citations4
Total Downloads183
Last 12 Months38
Last 6 weeks10

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Derandomizing stochastic prediction strategies

V. Vovk

Pages 32–44https://doi.org/10.1145/267460.267473

- 12
- 354
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Total Citations12
Total Downloads354
Last 12 Months59
Last 6 weeks16

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On-line learning and the metrical task system problem

Avrim Blum,
Carl Burch

Pages 45–53https://doi.org/10.1145/267460.267475

- 20
- 440
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Total Citations20
Total Downloads440
Last 12 Months138
Last 6 weeks22

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On the complexity of learning for a spiking neuron (extended abstract)

Wolfgang Maass,
Michael Schmitt

Pages 54–61https://doi.org/10.1145/267460.267477

- 5
- 414
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Total Citations5
Total Downloads414
Last 12 Months37
Last 6 weeks11

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Learning probabilistically consistent linear threshold functions

Tom Bylander

Pages 62–71https://doi.org/10.1145/267460.267479

- 1
- 290
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Total Citations1
Total Downloads290
Last 12 Months65
Last 6 weeks11

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PAC adaptive control of linear systems

Claude-Nicolas Fiechter

Pages 72–80https://doi.org/10.1145/267460.267481

- 21
- 626
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Total Citations21
Total Downloads626
Last 12 Months121
Last 6 weeks24

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FINite learning capabilities and their limits

Robert Daley,
Bala Kalyanasundaram

Pages 81–89https://doi.org/10.1145/267460.267483

- 2
- 176
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Total Citations2
Total Downloads176
Last 12 Months29
Last 6 weeks9

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Asymmetric team learning

Kalvis Apsītis,
Rūsiņš Freivalds,
Carl H. Smith

Pages 90–95https://doi.org/10.1145/267460.267484

- 1
- 250
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Total Citations1
Total Downloads250
Last 12 Months47
Last 6 weeks25

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Generalized notions of mind change complexity

Arun Sharma,
Frank Stephan,
Yuri Ventsov

Pages 96–108https://doi.org/10.1145/267460.267485

- 12
- 259
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Total Citations12
Total Downloads259
Last 12 Months35
Last 6 weeks11

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A brief look at some machine learning problems in genomics

David Haussler

Pages 109–113https://doi.org/10.1145/267460.267486

- 2
- 538
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Total Citations2
Total Downloads538
Last 12 Months89
Last 6 weeks14

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An efficient extension to mixture techniques for prediction and decision trees

Fernando Pereira,
Yoram Singer

Pages 114–121https://doi.org/10.1145/267460.267487

- 6
- 267
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Total Citations6
Total Downloads267
Last 12 Months58
Last 6 weeks14

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Performance bounds for nonlinear time series prediction

Ron Meir

Pages 122–129https://doi.org/10.1145/267460.267488

- 9
- 445
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Total Citations9
Total Downloads445
Last 12 Months65
Last 6 weeks11

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Computational sample complexity

Scott Decatur,
Oded Goldreich,
Dana Ron

Pages 130–142https://doi.org/10.1145/267460.267489

- 3
- 454
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Total Citations3
Total Downloads454
Last 12 Months94
Last 6 weeks16

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Dense shattering and teaching dimensions for differentiable families (extended abstract)

A. Kowalczyk

Pages 143–151https://doi.org/10.1145/267460.267490

- 0
- 236
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Total Citations0
Total Downloads236
Last 12 Months47
Last 6 weeks12

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Algorithmic stability and sanity-check bounds for leave-one-out cross-validation

Michael Kearns,
Dana Ron

Pages 152–162https://doi.org/10.1145/267460.267491

- 69
- 1,226
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Total Citations69
Total Downloads1,226
Last 12 Months387
Last 6 weeks60

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Analysis of two gradient-based algorithms for on-line regression

Nicolò Cesa-Bianchi

Pages 163–170https://doi.org/10.1145/267460.267492

- 9
- 400
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Total Citations9
Total Downloads400
Last 12 Months90
Last 6 weeks16

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General convergence results for linear discriminant updates

Adam J. Grove,
Nick Littlestone,
Dale Schuurmans

Pages 171–183https://doi.org/10.1145/267460.267493

- 32
- 415
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Total Citations32
Total Downloads415
Last 12 Months78
Last 6 weeks17

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The binary exponentiated gradient algorithm for learning linear functions

Tom Bylander

Pages 184–192https://doi.org/10.1145/267460.267495

- 12
- 284
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Total Citations12
Total Downloads284
Last 12 Months50
Last 6 weeks18

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A dichotomy theorem for learning quantified Boolean formulas

Víctor Dalmau

Pages 193–200https://doi.org/10.1145/267460.267496

- 12
- 236
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Total Citations12
Total Downloads236
Last 12 Months49
Last 6 weeks18

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Learning with maximum-entropy distributions

Yishay Mansour,
Mariano Schain

Pages 201–210https://doi.org/10.1145/267460.267499

- 0
- 351
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Total Citations0
Total Downloads351
Last 12 Months44
Last 6 weeks13

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Generating all maximal independent sets of bounded-degree hypergraphs

Nina Mishra,
Leonard Pitt

Pages 211–217https://doi.org/10.1145/267460.267500

- 17
- 528
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Total Citations17
Total Downloads528
Last 12 Months38
Last 6 weeks12

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Some label efficient learning results

David Helmbold,
Sandra Panizza

Pages 218–230https://doi.org/10.1145/267460.267502

- 23
- 354
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Total Citations23
Total Downloads354
Last 12 Months62
Last 6 weeks11

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Learning from examples with unspecified attribute values (extended abstract)

Sally A. Goldman,
Stephen S. Kwek,
Stephen D. Scott

Pages 231–242https://doi.org/10.1145/267460.267504

- 10
- 315
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Total Citations10
Total Downloads315
Last 12 Months59
Last 6 weeks13

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Learning distributions from random walks

Funda Ergün,
S. Ravi Kumar,
Ronitt Rubinfeld

Pages 243–249https://doi.org/10.1145/267460.267506

- 0
- 314
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Total Citations0
Total Downloads314
Last 12 Months32
Last 6 weeks12

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Distributed cooperative Bayesian learning strategies

Kenji Yamanishi

Pages 250–262https://doi.org/10.1145/267460.267507

- 14
- 680
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Total Citations14
Total Downloads680
Last 12 Months74
Last 6 weeks22

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Resource bounded next value and explanatory identification: learning automata, patterns and polynomials on-line

Susanne Kaufmann,
Frank Stephan

Pages 263–274https://doi.org/10.1145/267460.267509

- 2
- 214
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Total Citations2
Total Downloads214
Last 12 Months48
Last 6 weeks12

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Inferring answers to queries

William I. Gasarch,
Andrew C. Y. Lee

Pages 275–284https://doi.org/10.1145/267460.267512

- 4
- 246
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Total Citations4
Total Downloads246
Last 12 Months54
Last 6 weeks19

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Teachers, learners and black boxes

Dana Angluin,
Mārtiņš Kriķis

Pages 285–297https://doi.org/10.1145/267460.267515

- 12
- 489
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Total Citations12
Total Downloads489
Last 12 Months72
Last 6 weeks26

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Cited By

Zhang H A New Methodology for the Study of Dynamic Decision-Making with a Continuous Unknown Parameter, SSRN Electronic Journal, 10.2139/ssrn.3679048

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Contributors

Yoav Freund
University of California, San Diego
- Publication Years1990 - 2024
- Publication counts72
- Citation count8,246
- Available for Download21
- Downloads (cumulative)19,521
- Downloads (12 months)2,432
- Downloads (6 weeks)345
- Average Downloads per Article930
- Average Citation per Article115
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Robert Elias Schapire
Microsoft Research
- Publication Years1987 - 2024
- Publication counts143
- Citation count15,267
- Available for Download39
- Downloads (cumulative)50,860
- Downloads (12 months)7,157
- Downloads (6 weeks)912
- Average Downloads per Article1,304
- Average Citation per Article107
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Proceedings of the tenth annual conference on Computational learning theory

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Acceptance Rates

Overall Acceptance Rate 35 of 71 submissions, 49%

Year	Submitted	Accepted	Rate
COLT '99	71	35	49%
Overall	71	35	49%

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