Michael Kearns
Title
Cited by
Cited by
Year
An introduction to computational learning theory
MJ Kearns, UV Vazirani, U Vazirani
MIT press, 1994
19551994
Cryptographic limitations on learning Boolean formulae and finite automata
M Kearns, L Valiant
Journal of the ACM (JACM) 41 (1), 67-95, 1994
11121994
Near-optimal reinforcement learning in polynomial time
M Kearns, S Singh
Machine learning 49 (2), 209-232, 2002
10172002
Efficient noise-tolerant learning from statistical queries
M Kearns
Journal of the ACM (JACM) 45 (6), 983-1006, 1998
8841998
Graphical models for game theory
M Kearns, ML Littman, S Singh
arXiv preprint arXiv:1301.2281, 2013
7122013
A sparse sampling algorithm for near-optimal planning in large Markov decision processes
M Kearns, Y Mansour, AY Ng
Machine learning 49 (2), 193-208, 2002
6382002
A general lower bound on the number of examples needed for learning
A Ehrenfeucht, D Haussler, M Kearns, L Valiant
Information and Computation 82 (3), 247-261, 1989
5841989
Toward efficient agnostic learning
MJ Kearns, RE Schapire, LM Sellie
Machine Learning 17 (2-3), 115-141, 1994
5821994
Learning in the presence of malicious errors
M Kearns, M Li
SIAM Journal on Computing 22 (4), 807-837, 1993
5451993
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
M Kearns, D Ron
Neural computation 11 (6), 1427-1453, 1999
5331999
Optimizing dialogue management with reinforcement learning: Experiments with the NJFun system
S Singh, D Litman, M Kearns, M Walker
Journal of Artificial Intelligence Research 16, 105-133, 2002
4282002
On the complexity of teaching
SA Goldman, MJ Kearns
Journal of Computer and System Sciences 50 (1), 20-31, 1995
3711995
On the learnability of Boolean formulae
M Kearns, M Li, L Pitt, L Valiant
Proceedings of the nineteenth annual ACM symposium on Theory of computing …, 1987
3681987
Fairness in criminal justice risk assessments: The state of the art
R Berk, H Heidari, S Jabbari, M Kearns, A Roth
Sociological Methods & Research, 0049124118782533, 2018
3602018
Modeling the IT value paradox
ME Thatcher, DE Pingry
Communications of the ACM 50 (8), 41-45, 2007
353*2007
Nash Convergence of Gradient Dynamics in General-Sum Games.
SP Singh, MJ Kearns, Y Mansour
UAI, 541-548, 2000
3212000
Cryptographic primitives based on hard learning problems
A Blum, M Furst, M Kearns, RJ Lipton
Annual International Cryptology Conference, 278-291, 1993
3151993
An experimental study of the coloring problem on human subject networks
M Kearns, S Suri, N Montfort
science 313 (5788), 824-827, 2006
3082006
Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension
D Haussler, M Kearns, RE Schapire
Machine learning 14 (1), 83-113, 1994
3081994
Advances in Neural Information Processing Systems 10: Proceedings of the 1997 Conference
MI Jordan, MJ Kearns, SA Solla
Mit Press, 1998
3011998
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