Michael Kearns
TitleCited byYear
An introduction to computational learning theory
MJ Kearns, UV Vazirani, U Vazirani
MIT press, 1994
17771994
Cryptographic limitations on learning Boolean formulae and finite automata
M Kearns, L Valiant
Journal of the ACM (JACM) 41 (1), 67-95, 1994
10331994
Near-optimal reinforcement learning in polynomial time
M Kearns, S Singh
Machine learning 49 (2-3), 209-232, 2002
7992002
Efficient noise-tolerant learning from statistical queries
M Kearns
Journal of the ACM (JACM) 45 (6), 983-1006, 1998
7551998
Graphical models for game theory
M Kearns, ML Littman, S Singh
arXiv preprint arXiv:1301.2281, 2013
6382013
A sparse sampling algorithm for near-optimal planning in large Markov decision processes
M Kearns, Y Mansour, AY Ng
Machine learning 49 (2-3), 193-208, 2002
5612002
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
5351989
Toward efficient agnostic learning
MJ Kearns, RE Schapire, LM Sellie
Machine Learning 17 (2-3), 115-141, 1994
5151994
Learning in the presence of malicious errors
M Kearns, M Li
SIAM Journal on Computing 22 (4), 807-837, 1993
4951993
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
M Kearns, D Ron
Neural computation 11 (6), 1427-1453, 1999
4541999
Efficient distribution-free learning of probabilistic concepts
MJ Kearns, RE Schapire
Journal of Computer and System Sciences 48 (3), 464-497, 1994
4271994
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
3732002
On the learnability of Boolean formulae
M Kearns, M Li, L Pitt, L Valiant
Annual ACM Symposium on Theory of Computing: Proceedings of the nineteenth …, 1987
3731987
On the complexity of teaching
SA Goldman, MJ Kearns
Journal of Computer and System Sciences 50 (1), 20-31, 1995
3201995
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
2941994
Nash convergence of gradient dynamics in general-sum games
S Singh, M Kearns, Y Mansour
Proceedings of the Sixteenth conference on Uncertainty in artificial …, 2000
2882000
The magazine archive includes every article published in Communications of the ACM for over the past 50 years.
ME Thatcher, DE Pingry
Communications of the ACM 50 (8), 41-45, 2007
284*2007
An experimental study of the coloring problem on human subject networks
M Kearns, S Suri, N Montfort
Science 313 (5788), 824-827, 2006
2732006
Cryptographic primitives based on hard learning problems
A Blum, M Furst, M Kearns, RJ Lipton
Annual International Cryptology Conference, 278-291, 1993
2731993
On the boosting ability of top–down decision tree learning algorithms
M Kearns, Y Mansour
Journal of Computer and System Sciences 58 (1), 109-128, 1999
2681999
The system can't perform the operation now. Try again later.
Articles 1–20