Nisarg Shah

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Ariel ProcacciaGordon McKay Professor of Computer Science, Harvard UniversityVerified email at seas.harvard.edu
Ioannis CaragiannisProfessor of Computer Science, Aarhus UniversityVerified email at cs.au.dk
Rupert FreemanUniversity of VirginiaVerified email at darden.virginia.edu
David KurokawaComputer Science PhD Student, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Evi MichaUniversity of TorontoVerified email at cs.toronto.edu
Vincent ConitzerCarnegie Mellon UniversityVerified email at cs.cmu.edu
Daniel HalpernHarvard UniversityVerified email at g.harvard.edu
Debmalya MandalMax Planck Institute for Software SystemsVerified email at mpi-sws.org
Safwan HossainHarvard UniversityVerified email at g.harvard.edu
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Herve MoulinUniversity of GlasgowVerified email at glasgow.ac.uk
Ian KashUniversity of Illinois at ChicagoVerified email at uic.edu
Swaprava NathAssistant Professor, CSE, IIT BombayVerified email at cse.iitb.ac.in
Allan BorodinProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Albert X. JiangAssistant Professor of Computer Science, Trinity UniversityVerified email at trinity.edu
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchVerified email at harvard.edu
Dominik PetersCNRS, LAMSADE, Paris-DauphineVerified email at cnrs.fr
Yoram BachrachDeepMindVerified email at google.com
Gerdus BenadeAssistant Professor, Boston UniversityVerified email at bu.edu
Alexandros A. VoudourisCSEE, University of EssexVerified email at essex.ac.uk

Nisarg Shah

Assistant Professor, University of Toronto

Verified email at cs.toronto.edu - Homepage

Algorithmic Economics Artificial Intelligence Computational Social Choice Algorithmic Fairness


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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	460	2019
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	250	2015
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	178	2014
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	157	2016
Preference Elicitation for Participatory Budgeting G Benade, S Nath, AD Procaccia, N Shah Management Science 67 (5), 2813-2827, 2021	108	2021
Fair Public Decision Making V Conitzer, R Freeman, N Shah Proceedings of the 18th ACM Conference on Electronic Commerce, 629-646, 2017	108	2017
Subset selection via implicit utilitarian voting I Caragiannis, S Nath, AD Procaccia, N Shah Journal of Artificial Intelligence Research 58, 123-152, 2017	89	2017
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	86	2018
A Maximum Likelihood Approach For Selecting Sets of Alternatives AD Procaccia, S Reddy, N Shah Conference on Uncertainty in Artificial Intelligence, 695-704, 2012	82	2012
Participatory Budgeting: Models and Approaches H Aziz, N Shah Pathways Between Social Science and Computational Social Science, 215-236, 2021	78	2021
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	72	2018
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	55*	2019
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	54	2018
NTIRE 2022 challenge on perceptual image quality assessment J Gu, H Cai, C Dong, JS Ren, R Timofte, Y Gong, S Lao, S Shi, J Wang, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022	52	2022
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	50	2020
Diverse randomized agents vote to win A Jiang, L Soriano Marcolino, AD Procaccia, T Sandholm, N Shah, ... Advances in Neural Information Processing Systems 27, 2014	48	2014
Modal ranking: A uniquely robust voting rule I Caragiannis, A Procaccia, N Shah Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014	45	2014
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	41	2021
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	36	2019
Defender (mis) coordination in security games AX Jiang, AD Procaccia, Y Qian, N Shah, M Tambe Carnegie Mellon University, 2013	35	2013

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