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Nisarg Shah
Nisarg Shah
Associate Professor, University of Toronto
Bestätigte E-Mail-Adresse bei cs.toronto.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
The Unreasonable Fairness of Maximum Nash Welfare
I Caragiannis, D Kurokawa, H Moulin, AD Procaccia, N Shah, J Wang
ACM Transactions on Economics and Computation (TEAC) 7 (3), 1-32, 2019
7822019
Beyond dominant resource fairness: Extensions, limitations, and indivisibilities
DC Parkes, AD Procaccia, N Shah
ACM Transactions on Economics and Computation (TEAC) 3 (1), 1-22, 2015
2852015
No agent left behind: Dynamic fair division of multiple resources
I Kash, AD Procaccia, N Shah
Journal of Artificial Intelligence Research 51, 579-603, 2014
2242014
Participatory Budgeting: Models and Approaches
H Aziz, N Shah
Pathways Between Social Science and Computational Social Science, 215-236, 2021
1912021
Fair Public Decision Making
V Conitzer, R Freeman, N Shah
Proceedings of the 18th ACM Conference on Electronic Commerce, 629-646, 2017
1892017
Preference Elicitation for Participatory Budgeting
G Benade, S Nath, AD Procaccia, N Shah
Management Science 67 (5), 2813-2827, 2021
1772021
When do noisy votes reveal the truth?
I Caragiannis, AD Procaccia, N Shah
ACM Transactions on Economics and Computation (TEAC) 4 (3), 1-30, 2016
1722016
Fair Allocation of Indivisible Public Goods
B Fain, K Munagala, N Shah
Proceedings of the 2018 ACM Conference on Economics and Computation, 575-592, 2018
1342018
Subset selection via implicit utilitarian voting
I Caragiannis, S Nath, AD Procaccia, N Shah
Journal of Artificial Intelligence Research 58, 123-152, 2017
1262017
Distortion in social choice problems: The first 15 years and beyond
E Anshelevich, A Filos-Ratsikas, N Shah, AA Voudouris
arXiv preprint arXiv:2103.00911, 2021
1012021
Fair division with binary valuations: One rule to rule them all
D Halpern, AD Procaccia, A Psomas, N Shah
Web and Internet Economics: 16th International Conference, WINE 2020 …, 2020
962020
A Maximum Likelihood Approach For Selecting Sets of Alternatives
AD Procaccia, S Reddy, N Shah
Conference on Uncertainty in Artificial Intelligence, 695-704, 2012
922012
Leximin Allocations in the Real World
D Kurokawa, AD Procaccia, N Shah
ACM Transactions on Economics and Computation (TEAC) 6 (3-4), 1-24, 2018
892018
Group Fairness for the Allocation of Indivisible Goods
V Conitzer, R Freeman, N Shah, JW Vaughan
Proceedings of the AAAI Conference on Artificial Intelligence 33, 1853-1860, 2019
822019
Strategyproof Linear Regression in High Dimensions
Y Chen, C Podimata, AD Procaccia, N Shah
Proceedings of the 2018 ACM Conference on Economics and Computation, 9-26, 2018
812018
Resolving the optimal metric distortion conjecture
V Gkatzelis, D Halpern, N Shah
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020
792020
Best of both worlds: Ex-ante and ex-post fairness in resource allocation
R Freeman, N Shah, R Vaish
Proceedings of the 21st ACM Conference on Economics and Computation, 21-22, 2020
682020
Peer Prediction with Heterogeneous Users
A Agarwal, D Mandal, DC Parkes, N Shah
ACM Transactions on Economics and Computation (TEAC) 8 (1), 1-34, 2020
622020
Optimal bounds on the price of fairness for indivisible goods
S Barman, U Bhaskar, N Shah
International Conference on Web and Internet Economics, 356-369, 2020
602020
Efficient and Thrifty Voting by Any Means Necessary
D Mandal, AD Procaccia, N Shah, D Woodruff
Advances in Neural Information Processing Systems, 7178-7189, 2019
582019
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