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Shahin Jabbari
Shahin Jabbari
Verified email at seas.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Fairness in Criminal Justice Risk Assessments: The State of the Art
R Berk, H Heidari, S Jabbari, M Kearns, A Roth
Sociological Methods & Research 50 (1), 3-44, 2018
6552018
Adaptive Task Assignment for Crowdsourced Classification
CJ Ho, S Jabbari, JW Vaughan
30th International Conference on Machine Learning (ICML-13), 534-542, 2013
3112013
A Convex Framework for Fair Regression
R Berk, H Heidari, S Jabbari, M Joseph, M Kearns, J Morgenstern, S Neel, ...
Fairness, Accountability, and Transparency in Machine Learning (FATML-17), 2017
2272017
Fairness in Reinforcement Learning
S Jabbari, M Joseph, M Kearns, J Morgenstern, A Roth
34th International Conference on Machine Learning (ICML-17), 1617-1626, 2017
162*2017
Modeling Between-Population Variation in COVID-19 Dynamics in Hubei, Lombardy, and New York City
B Wilder, M Charpignon, J Killian, HC Ou, A Mate, S Jabbari, A Perrault, ...
Proceedings of the National Academy of Sciences (PNAS) 117 (41), 25904-25910, 2020
98*2020
Fair Algorithms for Learning in Allocation Problems
H Elzayn, S Jabbari, C Jung, M Kearns, S Neel, A Roth, Z Schutzman
2nd ACM Conference on Fairness, Accountability, and Transparency (FAT*-19 …, 2019
592019
Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets
S Assadi, J Hsu, S Jabbari
3rd AAAI Conference on Human Computation and Crowdsourcing (HCOMP-15), 12-21, 2015
462015
Strategic Network Formation with Attack and Immunization
S Goyal, S Jabbari, M Kearns, S Khanna, J Morgenstern
12th Conference on Web and Internet Economics (WINE-16), 429-443, 2016
362016
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
S Agarwal, S Jabbari, C Agarwal, S Upadhyay, ZS Wu, H Lakkaraju
38th International Conference on Machine Learning (ICML-21), 110-119, 2021
192021
Fair Influence Maximization: A Welfare Optimization Approach
A Rahmattalabi, S Jabbari, H Lakkaraju, P Vayanos, E Rice, M Tambe
35th AAAI Conference on Artificial Intelligence (AAAI-21), 11630-11638, 2021
19*2021
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
S Krishna, T Han, A Gu, J Pombra, S Jabbari, S Wu, H Lakkaraju
arXiv preprint arXiv:2202.01602, 2022
162022
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs
S Jabbari, R Rogers, A Roth, ZS Wu
30th Annual Conference on Neural Information Processing Systems (NIPS-16 …, 2016
102016
Solving Sudoku Using Probabilistic Graphical Models
S Khan, S Jabbari, S Jabbari, M Ghanbarinejad
Technical Report, 2014
7*2014
PAC Learning with General Class Noise Models
S Jabbari, RC Holte, S Zilles
35th German Conference on Artificial Intelligence (KI-2012), 73-84, 2012
62012
An Empirical Study of the Trade-Offs Between Interpretability and Fairness
S Jabbari, HC Ou, H Lakkaraju, M Tambe
5th Workshop on Human Interpretability in Machine Learning (WHI 2020 @ICML), 2020
52020
Robust Lock-down Optimization for COVID-19 Policy Guidance
A Bhardwaj, HC Ou, H Chen, S Jabbari, M Tambe, R Panicker, A Raval
AAAI Fall Symposium, 2020
52020
Network Formation under Random Attack and Probabilistic Spread
Y Chen, S Jabbari, M Kearns, S Khanna, J Morgenstern
28th International Joint Conference on Artificial Intelligence (IJCAI-19 …, 2019
52019
Equilibrium Characterization for Data Acquisition Games
J Dong, H Elzayn, S Jabbari, M Kearns, Z Schutzman
28th International Joint Conference on Artificial Intelligence (IJCAI-19 …, 2019
32019
Solving Structured Hierarchical Games Using Differential Backward Induction
Z Li, F Jia, A Mate, S Jabbari, M Chakraborty, M Tambe, Y Vorobeychik
38th Conference on Uncertainty in Artificial Intelligence (UAI-22), 2022
22022
A Game-Theoretic Approach for Hierarchical Policy-Making
F Jia, A Mate, Z Li, S Jabbari, M Chakraborty, M Tambe, M Wellman, ...
arXiv preprint arXiv:2102.10646, 2021
22021
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