Nika Haghtalab 个人学术档案

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Ariel ProcacciaGordon McKay Professor of Computer Science, Harvard University在 seas.harvard.edu 的电子邮件经过验证
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at Chicago在 ttic.edu 的电子邮件经过验证
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
pranjal awasthiGoogle在 rutgers.edu 的电子邮件经过验证
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Miroslav DudikMicrosoft Research在 microsoft.com 的电子邮件经过验证
Vasilis SyrgkanisAssistant Professor, Stanford University在 stanford.edu 的电子邮件经过验证
Robert SchapireMicrosoft Research在 microsoft.com 的电子邮件经过验证
Haipeng LuoAssociate Professor, University of Southern California在 usc.edu 的电子邮件经过验证
Colin WhiteAbacus.AI在 cs.cmu.edu 的电子邮件经过验证
Ruth UrnerAssociate Professor, York University, Toronto在 eecs.yorku.ca 的电子邮件经过验证
Hongyang ZhangAssistant Professor of Computer Science, University of Waterloo在 uwaterloo.ca 的电子邮件经过验证
Ankit SharmaGoogle Inc.在 google.com 的电子邮件经过验证
John P. DickersonAssociate Professor of Computer Science, University of Maryland & Chief Scientist, Arthur AI在 cs.umd.edu 的电子邮件经过验证
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google Research在 harvard.edu 的电子邮件经过验证
Fei FangCarnegie Mellon University在 cmu.edu 的电子邮件经过验证
Thanh NguyenComputer Science, University of Oregon在 cs.uoregon.edu 的电子邮件经过验证
Arunesh SinhaRutgers University在 rutgers.edu 的电子邮件经过验证
Shai Ben-DavidUniverity of Waterloo, Canada在 uwaterloo.ca 的电子邮件经过验证
Ioannis CaragiannisProfessor of Computer Science, Aarhus University在 cs.au.dk 的电子邮件经过验证

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Nika Haghtalab

University of California, Berkeley

在 berkeley.edu 的电子邮件经过验证 - 首页

Learning theory Game theory Artificial Intelligence


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Jailbroken: How does llm safety training fail? A Wei, N Haghtalab, J Steinhardt Advances in Neural Information Processing Systems 36, 2024	322	2024
Commitment Without Regrets: Online Learning in Stackelberg Security Games MF Balcan, A Blum, N Haghtalab, AD Procaccia	137	2015
Learning optimal commitment to overcome insecurity A Blum, N Haghtalab, AD Procaccia Advances in Neural Information Processing Systems 27, 2014	111	2014
Efficient learning of linear separators under bounded noise P Awasthi, MF Balcan, N Haghtalab, R Urner Conference on Learning Theory, 167-190, 2015	101	2015
Learning and 1-bit compressed sensing under asymmetric noise P Awasthi, MF Balcan, N Haghtalab, H Zhang Conference on Learning Theory, 152-192, 2016	98	2016
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	86	2020
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	82	2015
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	77	2020
Maximizing welfare with incentive-aware evaluation mechanisms N Haghtalab, N Immorlica, B Lucier, JZ Wang arXiv preprint arXiv:2011.01956, 2020	69	2020
Collaborative PAC learning A Blum, N Haghtalab, AD Procaccia, M Qiao Advances in Neural Information Processing Systems 30, 2017	61	2017
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	56	2018
Smoothed analysis of online and differentially private learning N Haghtalab, T Roughgarden, A Shetty Advances in Neural Information Processing Systems 33, 9203-9215, 2020	50	2020
Smoothed analysis with adaptive adversaries N Haghtalab, T Roughgarden, A Shetty 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022	45	2022
Online learning with a hint O Dekel, N Haghtalab, P Jaillet Advances in Neural Information Processing Systems 30, 2017	45	2017
Three strategies to success: Learning adversary models in security games N Haghtalab, F Fang, TH Nguyen, A Sinha, AD Procaccia, M Tambe	45	2016
One for one, or all for all: Equilibria and optimality of collaboration in federated learning A Blum, N Haghtalab, RL Phillips, H Shao International Conference on Machine Learning, 1005-1014, 2021	41	2021
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	39	2019
Clustering in the Presence of Background Noise S Ben-David, N Haghtalab International Conference in Machine Learning (ICML 2014), 2014	35	2014
On-demand sampling: Learning optimally from multiple distributions N Haghtalab, M Jordan, E Zhao Advances in Neural Information Processing Systems 35, 406-419, 2022	32	2022
Lazy Defenders Are Almost Optimal Against Diligent Attackers A Blum, N Haghtalab, AD Procaccia 28th AAAI Conference on Artificial Intelligence, 2014	30	2014

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