Vincent Conitzer

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Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityEmail verificata su cs.cmu.edu
Lirong XiaProfessor of Computer Science, Rutgers University - New Brunswick; Deputy Director of DIMACSEmail verificata su rutgers.edu
Mingyu GuoSenior Lecturer at School of Computer and Mathematical Sciences, University of AdelaideEmail verificata su adelaide.edu.au
Jerome Langsenior researcher at CNRSEmail verificata su lamsade.dauphine.fr
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchEmail verificata su harvard.edu
Markus BrillUniversity of WarwickEmail verificata su warwick.ac.uk
Liad WagmanDean and Professor of Economics, Lally School of Management, Rensselaer Polytechnic InstituteEmail verificata su rpi.edu
Felix BrandtProfessor of Computer Science, Technische Universität MünchenEmail verificata su in.tum.de
Ariel ProcacciaGordon McKay Professor of Computer Science, Harvard UniversityEmail verificata su seas.harvard.edu
Makoto YokooKyushu UniversityEmail verificata su inf.kyushu-u.ac.jp
Ronald ParrProfessor of Computer Science, Duke UniversityEmail verificata su cs.duke.edu
Atsushi IwasakiUniversity of Electro-CommunicationsEmail verificata su is.uec.ac.jp
Toby WalshProfessor, UNSW and CSIRO Data61Email verificata su cse.unsw.edu.au
Fei FangCarnegie Mellon UniversityEmail verificata su cmu.edu
Kamesh MunagalaProfessor of Computer Science, Duke UniversityEmail verificata su cs.duke.edu
Christopher KiekintveldUniversity of Texas at El PasoEmail verificata su utep.edu
Zhengyu YinComputer Science USCEmail verificata su usc.edu
Shaddin DughmiAssociate Professor of Computer Science, University of Southern CaliforniaEmail verificata su usc.edu
Haifeng XuUniversity of ChicagoEmail verificata su uchicago.edu
Paolo SantiIIT - CNR, Pisa - Italy and MIT Senseable City LabEmail verificata su iit.cnr.it

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Vincent Conitzer

Professor of CS, Carnegie Mellon University; Professor of CS and Philosophy, University of Oxford

Email verificata su cs.cmu.edu - Home page

artificial intelligence computer science economics philosophy game theory


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Handbook of computational social choice F Brandt, V Conitzer, U Endriss, J Lang, AD Procaccia Cambridge University Press, 2016	1255	2016
Computing the optimal strategy to commit to V Conitzer, T Sandholm Proceedings of the 7th ACM conference on Electronic commerce, 82-90, 2006	660	2006
New complexity results about Nash equilibria V Conitzer, T Sandholm Games and Economic Behavior 63 (2), 621-641, 2008	610	2008
Complexity of mechanism design V Conitzer, T Sandholm arXiv preprint cs/0205075, 2002	422	2002
When are elections with few candidates hard to manipulate? V Conitzer, T Sandholm, J Lang Journal of the ACM (JACM) 54 (3), 14-es, 2007	419	2007
Justified representation in approval-based committee voting H Aziz, M Brill, V Conitzer, E Elkind, R Freeman, T Walsh Social Choice and Welfare 48 (2), 461-485, 2017	367	2017
AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents V Conitzer, T Sandholm Machine Learning 67, 23-43, 2007	364	2007
Stackelberg vs. Nash in security games: An extended investigation of interchangeability, equivalence, and uniqueness D Korzhyk, Z Yin, C Kiekintveld, V Conitzer, M Tambe Journal of Artificial Intelligence Research 41, 297-327, 2011	356	2011
Determining possible and necessary winners given partial orders L Xia, V Conitzer Journal of Artificial Intelligence Research 41, 25-67, 2011	285	2011
Computational social choice F Brandt, V Conitzer, U Endriss Multiagent systems 2, 213-84, 2012	275	2012
A double oracle algorithm for zero-sum security games on graphs M Jain, D Korzhyk, O Vaněk, V Conitzer, M Pěchouček, M Tambe The 10th International Conference on Autonomous Agents and Multiagent …, 2011	262	2011
Complexity of computing optimal stackelberg strategies in security resource allocation games D Korzhyk, V Conitzer, R Parr Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 805-810, 2010	251	2010
Improved bounds for computing Kemeny rankings V Conitzer, A Davenport, J Kalagnanam AAAI 6, 620-626, 2006	248	2006
Common voting rules as maximum likelihood estimators V Conitzer, T Sandholm arXiv preprint arXiv:1207.1368, 2012	239	2012
Hide and seek: Costly consumer privacy in a market with repeat purchases V Conitzer, CR Taylor, L Wagman Marketing Science 31 (2), 277-292, 2012	231	2012
Moral decision making frameworks for artificial intelligence V Conitzer, W Sinnott-Armstrong, JS Borg, Y Deng, M Kramer Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	228	2017
Mixed-integer programming methods for finding Nash equilibria T Sandholm, A Gilpin, V Conitzer AAAI, 495-501, 2005	219	2005
Preference Functions that Score Rankings and Maximum Likelihood Estimation. V Conitzer, M Rognlie, L Xia IJCAI 9, 109-115, 2009	218	2009
Computing Shapley values, manipulating value division schemes, and checking core membership in multi-issue domains V Conitzer, T Sandholm AAAI 4, 219-225, 2004	194	2004
Vote elicitation: Complexity and strategy-proofness V Conitzer, T Sandholm AAAI/IAAI, 392-397, 2002	191	2002

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