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 ConitzerDuke UniversityVerified email at cs.duke.edu
Daniel HalpernHarvard UniversityVerified email at g.harvard.edu
Safwan HossainHarvard UniversityVerified email at g.harvard.edu
Debmalya MandalMax Planck Institute for Software SystemsVerified email at mpi-sws.org
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 TambeDirector CRCS Center @Harvard; Director "AI for Social Good" @Google India ResearchVerified email at harvard.edu
Yoram BachrachDeepMindVerified email at google.com
Gerdus BenadeAssistant Professor, Boston UniversityVerified email at bu.edu
Manas JoglekarPhD, Stanford UniversityVerified email at stanford.edu
Dominik PetersCNRS, LAMSADE, Paris-DauphineVerified email at cnrs.fr

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	448	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	245	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	173	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	153	2016
Fair Public Decision Making V Conitzer, R Freeman, N Shah Proceedings of the 18th ACM Conference on Electronic Commerce, 629-646, 2017	108	2017
Preference Elicitation for Participatory Budgeting G Benade, S Nath, AD Procaccia, N Shah Management Science 67 (5), 2813-2827, 2021	106	2021
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	87	2018
Subset selection via implicit utilitarian voting I Caragiannis, S Nath, AD Procaccia, N Shah Journal of Artificial Intelligence Research 58, 123-152, 2017	85	2017
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	76	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	74	2018
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	55	2018
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
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	50*	2019
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	49	2022
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	49	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
Truthful univariate estimators I Caragiannis, A Procaccia, N Shah International Conference on Machine Learning, 127-135, 2016	35	2016
Defender (mis) coordination in security games AX Jiang, AD Procaccia, Y Qian, N Shah, M Tambe Twenty-Third International Joint Conference on Artificial Intelligence, 2013	35	2013
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	34	2021

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