Nika Haghtalab

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Ariel ProcacciaGordon McKay Professor of Computer Science, Harvard UniversityVerifierad e-postadress på seas.harvard.edu
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at ChicagoVerifierad e-postadress på ttic.edu
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
pranjal awasthiRutgers UniversityVerifierad e-postadress på rutgers.edu
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
John P. DickersonAssociate Professor of Computer Science, University of Maryland & Chief Scientist, Arthur AIVerifierad e-postadress på cs.umd.edu
Miroslav DudikMicrosoft ResearchVerifierad e-postadress på microsoft.com
Vasilis SyrgkanisMicrosoft ResearchVerifierad e-postadress på microsoft.com
Robert SchapireMicrosoft ResearchVerifierad e-postadress på microsoft.com
Haipeng LuoUniversity of Southern CaliforniaVerifierad e-postadress på usc.edu
Colin WhiteAbacus.AIVerifierad e-postadress på cs.cmu.edu
Ruth UrnerAssistant Professor, York University, TorontoVerifierad e-postadress på eecs.yorku.ca
Hongyang ZhangAssistant Professor of Computer Science, University of Waterloo, Vector InstituteVerifierad e-postadress på uwaterloo.ca
Milind TambeDirector CRCS Center @Harvard; Director "AI for Social Good" @Google India ResearchVerifierad e-postadress på harvard.edu
Fei FangCarnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Thanh NguyenComputer and Information Science, University of OregonVerifierad e-postadress på cs.uoregon.edu
Arunesh SinhaSingapore Management UniversityVerifierad e-postadress på smu.edu.sg
Shai Ben-DavidUniverity of Waterloo, CanadaVerifierad e-postadress på uwaterloo.ca
Ioannis CaragiannisProfessor, Aarhus UniversityVerifierad e-postadress på cs.au.dk
Rohit VaishAssistant Professor, IIT DelhiVerifierad e-postadress på iitd.ac.in

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Nika Haghtalab

University of California, Berkeley

Verifierad e-postadress på berkeley.edu - Startsida

Learning theory Game theory Artificial Intelligence


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Commitment Without Regrets: Online Learning in Stackelberg Security Games MF Balcan, A Blum, N Haghtalab, AD Procaccia	89	2015
Efficient learning of linear separators under bounded noise P Awasthi, MF Balcan, N Haghtalab, R Urner Conference on Learning Theory, 167-190, 2015	85	2015
Learning optimal commitment to overcome insecurity A Blum, N Haghtalab, AD Procaccia Advances in Neural Information Processing Systems 27, 2014	84	2014
Learning and 1-bit compressed sensing under asymmetric noise P Awasthi, MF Balcan, N Haghtalab, H Zhang Conference on Learning Theory, 152-192, 2016	80	2016
Ignorance is almost bliss: Near-optimal stochastic matching with few queries A Blum, JP Dickerson, N Haghtalab, AD Procaccia, T Sandholm, ... Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015	55	2015
The disparate equilibria of algorithmic decision making when individuals invest rationally LT Liu, A Wilson, N Haghtalab, AT Kalai, C Borgs, J Chayes Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020	49	2020
Oracle-efficient online learning and auction design M Dudík, N Haghtalab, H Luo, RE Schapire, V Syrgkanis, JW Vaughan Journal of the ACM (JACM) 67 (5), 1-57, 2020	48	2020
Maximizing welfare with incentive-aware evaluation mechanisms N Haghtalab, N Immorlica, B Lucier, JZ Wang arXiv preprint arXiv:2011.01956, 2020	41	2020
The provable virtue of laziness in motion planning N Haghtalab, S Mackenzie, A Procaccia, O Salzman, S Srinivasa Proceedings of the International Conference on Automated Planning and …, 2018	36	2018
Three strategies to success: Learning adversary models in security games N Haghtalab, F Fang, TH Nguyen, A Sinha, AD Procaccia, M Tambe	33	2016
Collaborative PAC learning A Blum, N Haghtalab, AD Procaccia, M Qiao Advances in Neural Information Processing Systems 30, 2017	30	2017
Clustering in the Presence of Background Noise S Ben-David, N Haghtalab International Conference in Machine Learning (ICML 2014), 2014	30	2014
Lazy Defenders Are Almost Optimal Against Diligent Attackers A Blum, N Haghtalab, AD Procaccia 28th AAAI Conference on Artificial Intelligence, 2014	29	2014
Online learning with a hint O Dekel, N Haghtalab, P Jaillet Advances in Neural Information Processing Systems 30, 2017	27	2017
Structured robust submodular maximization: Offline and online algorithms N Anari, N Haghtalab, S Naor, S Pokutta, M Singh, A Torrico The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	23	2019
Opting into optimal matchings A Blum, I Caragiannis, N Haghtalab, AD Procaccia, EB Procaccia, ... Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017	20	2017
Ignorance is almost bliss: Near-optimal stochastic matching with few queries A Blum, JP Dickerson, N Haghtalab, AD Procaccia, T Sandholm, ... Operations research 68 (1), 16-34, 2020	19	2020
Efficient PAC learning from the crowd P Awasthi, A Blum, N Haghtalab, Y Mansour Conference on Learning Theory, 127-150, 2017	18	2017
-center Clustering under Perturbation Resilience MF Balcan, N Haghtalab, C White arXiv preprint arXiv:1505.03924, 2015	18*	2015
Smoothed analysis of online and differentially private learning N Haghtalab, T Roughgarden, A Shetty Advances in Neural Information Processing Systems 33, 9203-9215, 2020	13	2020

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