Follow
Nika Haghtalab
Title
Cited by
Cited by
Year
Commitment Without Regrets: Online Learning in Stackelberg Security Games
MF Balcan, A Blum, N Haghtalab, AD Procaccia
1002015
Learning optimal commitment to overcome insecurity
A Blum, N Haghtalab, AD Procaccia
Advances in Neural Information Processing Systems 27, 2014
922014
Efficient learning of linear separators under bounded noise
P Awasthi, MF Balcan, N Haghtalab, R Urner
Conference on Learning Theory, 167-190, 2015
882015
Learning and 1-bit compressed sensing under asymmetric noise
P Awasthi, MF Balcan, N Haghtalab, H Zhang
Conference on Learning Theory, 152-192, 2016
842016
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
582015
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
562020
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
512020
Maximizing welfare with incentive-aware evaluation mechanisms
N Haghtalab, N Immorlica, B Lucier, JZ Wang
arXiv preprint arXiv:2011.01956, 2020
422020
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
392018
Collaborative PAC learning
A Blum, N Haghtalab, AD Procaccia, M Qiao
Advances in Neural Information Processing Systems 30, 2017
342017
Three strategies to success: Learning adversary models in security games
N Haghtalab, F Fang, TH Nguyen, A Sinha, AD Procaccia, M Tambe
342016
Online learning with a hint
O Dekel, N Haghtalab, P Jaillet
Advances in Neural Information Processing Systems 30, 2017
322017
Clustering in the Presence of Background Noise
S Ben-David, N Haghtalab
International Conference in Machine Learning (ICML 2014), 2014
312014
Lazy Defenders Are Almost Optimal Against Diligent Attackers
A Blum, N Haghtalab, AD Procaccia
28th AAAI Conference on Artificial Intelligence, 2014
292014
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
282019
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
232020
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
202017
Efficient PAC learning from the crowd
P Awasthi, A Blum, N Haghtalab, Y Mansour
Conference on Learning Theory, 127-150, 2017
192017
-center Clustering under Perturbation Resilience
MF Balcan, N Haghtalab, C White
arXiv preprint arXiv:1505.03924, 2015
19*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
172020
The system can't perform the operation now. Try again later.
Articles 1–20