Michael Kearns
Title
Cited by
Cited by
Year
An introduction to computational learning theory
MJ Kearns, UV Vazirani, U Vazirani
MIT press, 1994
18671994
Cryptographic limitations on learning Boolean formulae and finite automata
M Kearns, L Valiant
Journal of the ACM (JACM) 41 (1), 67-95, 1994
10851994
Near-optimal reinforcement learning in polynomial time
M Kearns, S Singh
Machine learning 49 (2-3), 209-232, 2002
9162002
Efficient noise-tolerant learning from statistical queries
M Kearns
Journal of the ACM (JACM) 45 (6), 983-1006, 1998
8201998
Graphical models for game theory
M Kearns, ML Littman, S Singh
arXiv preprint arXiv:1301.2281, 2013
6902013
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
6052002
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
5721989
Toward efficient agnostic learning
MJ Kearns, RE Schapire, LM Sellie
Machine Learning 17 (2-3), 115-141, 1994
5411994
Learning in the presence of malicious errors
M Kearns, M Li
SIAM Journal on Computing 22 (4), 807-837, 1993
5241993
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
M Kearns, D Ron
Neural computation 11 (6), 1427-1453, 1999
4851999
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
4102002
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
3781987
On the complexity of teaching
SA Goldman, MJ Kearns
3561992
Modeling the IT value paradox
ME Thatcher, DE Pingry
Communications of the ACM 50 (8), 41-45, 2007
322*2007
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
3031994
Nash Convergence of Gradient Dynamics in General-Sum Games.
SP Singh, MJ Kearns, Y Mansour
UAI, 541-548, 2000
3002000
An experimental study of the coloring problem on human subject networks
M Kearns, S Suri, N Montfort
science 313 (5788), 824-827, 2006
2962006
Cryptographic primitives based on hard learning problems
A Blum, M Furst, M Kearns, RJ Lipton
Annual International Cryptology Conference, 278-291, 1993
2891993
Efficient distribution-free learning of probabilistic concepts
MJ Kearns, RE Schapire
Journal of Computer and System Sciences 48 (3), 464-497, 1994
2831994
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
2821999
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