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Michael Kearns - Publications

Affiliations: 
Computer and Information Science University of Pennsylvania, Philadelphia, PA, United States 
Area:
Intelligent Systems: Machine Learning, Networks: Security and Privacy, Theory: Algorithms and Complexity
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27 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Dick T, Dwork C, Kearns M, Liu T, Roth A, Vietri G, Wu ZS. Reply to Sanchéz et al.: Multiplicity does not protect privacy. Proceedings of the National Academy of Sciences of the United States of America. 120: e2304263120. PMID 37094130 DOI: 10.1073/pnas.2304263120  0.448
2023 Dick T, Dwork C, Kearns M, Liu T, Roth A, Vietri G, Wu ZS. Confidence-ranked reconstruction of census microdata from published statistics. Proceedings of the National Academy of Sciences of the United States of America. 120: e2218605120. PMID 36800385 DOI: 10.1073/pnas.2218605120  0.505
2018 Berk R, Heidari H, Jabbari S, Kearns M, Roth A. Fairness in Criminal Justice Risk Assessments: The State of the Art Sociological Methods & Research. 4912411878253. DOI: 10.1177/0049124118782533  0.534
2016 Kearns M, Roth A, Wu ZS, Yaroslavtsev G. Private algorithms for the protected in social network search. Proceedings of the National Academy of Sciences of the United States of America. PMID 26755606 DOI: 10.1073/Pnas.1510612113  0.558
2016 Chen Y, Ghosh A, Kearns M, Roughgarden T, Vaughan JW. Mathematical foundations for social computing Communications of the Acm. 59: 102-108. DOI: 10.1145/2960403  0.578
2015 Amin K, Cummings R, Dworkin L, Kearns M, Roth A. Online learning and profit maximization from revealed preferences Proceedings of the National Conference On Artificial Intelligence. 2: 770-776.  0.575
2014 Kearns M, Pai MM, Roth A, Ullman J. Mechanism design in large games: Incentives and privacy American Economic Review. 104: 431-435. DOI: 10.1257/Aer.104.5.431  0.551
2011 Brautbar M, Kearns M. A clustering coefficient network formation game Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6982: 224-235. DOI: 10.1007/978-3-642-24829-0_21  0.689
2010 Chakraborty T, Judd S, Kearns M, Tan J. A behavioral study of bargaining in social networks Proceedings of the Acm Conference On Electronic Commerce. 243-251. DOI: 10.1145/1807342.1807382  0.563
2010 Ganchev K, Nevmyvaka Y, Kearns M, Vaughan JW. Censored exploration and the dark pool problem Communications of the Acm. 53: 99-107. DOI: 10.1145/1735223.1735247  0.62
2010 Brautbar M, Kearns M, Syed U. Private and third-party randomization in risk-sensitive equilibrium concepts Proceedings of the National Conference On Artificial Intelligence. 2: 723-728.  0.693
2009 Kearns M, Judd S, Tan J, Wortman J. Behavioral experiments on biased voting in networks. Proceedings of the National Academy of Sciences of the United States of America. 106: 1347-52. PMID 19168630 DOI: 10.1073/Pnas.0808147106  0.559
2006 Kearns M, Suri S, Montfort N. An experimental study of the coloring problem on human subject networks. Science (New York, N.Y.). 313: 824-7. PMID 16902134 DOI: 10.1126/Science.1127207  0.6
2006 Isbell CL, Kearns M, Singh S, Shelton CR, Stone P, Kormann D. Cobot in LambdaMOO: An adaptive social statistics agent Autonomous Agents and Multi-Agent Systems. 13: 327-354. DOI: 10.1007/S10458-006-0005-Z  0.329
2005 Kakade SM, Kearns M, Ortiz LE, Pemantle R, Suri S. Economic properties of social networks Advances in Neural Information Processing Systems.  0.572
2002 Singh S, Litman D, Kearns M, Walker M. Optimizing dialogue management with reinforcement learning: experiments with the NJFun system Journal of Artificial Intelligence Research. 16: 105-133. DOI: 10.1613/Jair.859  0.326
2002 Kearns M, Singh S. Machine Learning. 49: 209-232. DOI: 10.1023/A:1017984413808  0.315
2002 Kearns M, Mansour Y, Ng AY. Machine Learning. 49: 193-208. DOI: 10.1023/A:1017932429737  0.325
2000 Kearns M, Ron D. Testing Problems with Sublearning Sample Complexity Journal of Computer and System Sciences. 61: 428-456. DOI: 10.1006/Jcss.1999.1656  0.31
1999 Kearns M, Mansour Y. On the Boosting Ability of Top–Down Decision Tree Learning Algorithms Journal of Computer and System Sciences. 58: 109-128. DOI: 10.1006/Jcss.1997.1543  0.32
1998 Kearns M. Efficient noise-tolerant learning from statistical queries Journal of the Acm. 45: 983-1006. DOI: 10.1145/293347.293351  0.356
1997 Freund Y, Kearns M, Ron D, Rubinfeld R, Schapire RE, Sellie L. Efficient Learning of Typical Finite Automata from Random Walks Information and Computation. 138: 23-48. DOI: 10.1006/Inco.1997.2648  0.379
1994 Kearns M, Li M, Valiant L. Learning Boolean formulas Journal of the Acm (Jacm). 41: 1298-1328. DOI: 10.1145/195613.195656  0.645
1994 Kearns M, Valiant L. Cryptographic limitations on learning Boolean formulae and finite automata Journal of the Acm (Jacm). 41: 67-95. DOI: 10.1145/174644.174647  0.663
1993 Kearns M, Li M. Learning in the Presence of Malicious Errors Siam Journal On Computing. 22: 807-837. DOI: 10.1137/0222052  0.338
1991 Haussler D, Kearns M, Littlestone N, Warmuth MK. Equivalence of models for polynomial learnability Information and Computation. 95: 129-161. DOI: 10.1016/0890-5401(91)90042-Z  0.358
1989 Ehrenfeucht A, Haussler D, Kearns M, Valiant L. A general lower bound on the number of examples needed for learning Information and Computation. 82: 247-261. DOI: 10.1016/0890-5401(89)90002-3  0.614
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