|
|
Probabilistic Learning Theory, with Emphasis on Sample Complexity
– Martin Anthony
|
|
16
|
Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants
– Martin Anthony
- 1994
|
|
|
Learning Probabilistic Read-once Formulas on Product Distributions
– Robert E. Schapre, Ming Li, Leslie Valiant
|
|
169
|
Toward efficient agnostic learning
– Michael J. Kearns, Robert E. Schapire, Linda M. Sellie, Lisa Hellerstein
- 1992
|
|
14
|
On Restricted-Focus-of-Attention Learnability of Boolean Functions
– Andreas Birkendorf, Eli Dichterman, Jeffrey Jackson, Hans Ulrich Simon
- 1998
|
|
5
|
Learning with Limited Visibility
– Eli Dichterman
- 1998
|
|
29
|
Learning with Restricted Focus of Attention
– Shai Ben-David, Eli Dichterman
- 1997
|
|
248
|
Efficient noise-tolerant learning from statistical queries
– Michael Kearns
- 1998
|
|
1
|
Learning to be Competent
– Roni Khardon, Roni Khardon
- 1996
|
|
3
|
Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework
– David Haussler
- 1995
|
|
8
|
Computational Sample Complexity and Attribute-Efficient Learning
– Rocco A. Servedio, Rocco Servedio
- 2000
|
|
1
|
On Exploiting Knowledge and Concept Use in Learning Theory
– Leonard Pitt
|
|
37
|
Probably Approximately Correct Learning
– David Haussler
- 1990
|
|
43
|
Learning to Take Actions
– Roni Khardon
- 1998
|
|
|
The Fourier Transform in Computational Learning Theory
– Jennifer Sun
- 1996
|
|
3
|
Computational learning theory for artificial neural networks
– Martin Anthony, Norman Biggs
- 1993
|
|
|
The Approximability of Learning and Constraint Satisfaction Problems
– Yi Wu
- 2010
|
|
10
|
The learnability of quantum states
– Scott Aaronson
- 2006
|
|
|
Computational Learning Theory
– Sally A. Goldman
|