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8
|
A Sequential Sampling Algorithm for a General Class of Utility Criteria
– Tobias Scheffer, Stefan Wrobel
- 2000
|
|
|
A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases
– Tobias Scheffer, Stefan Wrobel
- 2002
|
|
|
Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems
– Tobias Scheffer, Stefan Wrobel
- 2001
|
|
5
|
Sequential Sampling Algorithms: Unified Analysis and Lower Bounds
– Ricard Gavalda, Osamu Watanabe
- 2001
|
|
|
Mining Complex Models from Arbitrarily Large Databases
– In Constant Time, Geoff Hulten, Pedro Domingos
- 2002
|
|
|
Heuristic Rule Learning
– Frederik Janssen
- 2012
|
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220
|
Mining high-speed data streams
– Pedro Domingos
- 2000
|
|
79
|
The Power of Decision Tables
– Ron Kohavi
- 1995
|
|
65
|
Extracting Comprehensible Models from Trained Neural Networks
– W. Craven
- 1996
|
|
776
|
Wrappers for feature subset selection
– Ron Kohavi , George H. John
- 1997
|
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35
|
Feature Subset Selection as Search with Probabilistic Estimates
– Ron Kohavi
- 1994
|
|
3
|
Error Estimation and Model Selection
– Tobias Scheffer, Vom Fachbereich Informatik, Doktor Der Naturwissenschaften, Vorsitzender Prof, Dr. Stefan Jahnichen, Berichter Prof, Dr. Fritz Wysotzki
- 1999
|
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24
|
Mobimine: Monitoring the stock market from a PDA
– Hillol Kargupta, Byung-hoon Park, Sweta Pittie, Lei Liu, Deepali Kushraj
- 2002
|
|
196
|
Mining time-changing data streams
– Geoff Hulten, Laurie Spencer, Pedro Domingos
- 2001
|
|
4
|
Distribution-Dependent Vapnik-Chervonenkis Bounds
– Nicolas Vayatis, Robert Azencott
- 1999
|
|
43
|
Sampling Algorithms: Lower Bounds and Applications (Extended Abstract)
– Ziv Bar-yossef, D. Sivakumar
- 2001
|
|
30
|
Introduction to Statistical Learning Theory
– Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi
- 2004
|
|
7
|
Simple Sampling Techniques for Discovery Science
– Osamu Watanabe
- 2000
|
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11
|
PALO: A Probabilistic Hill-Climbing Algorithm
– Russell Greiner
- 1995
|
