Aleksandrs Slivkins

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Robert KleinbergDepartment of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Zhiwei Steven WuCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityVerified email at microsoft.com
Moshe BabaioffHebrew University of JerusalemVerified email at mail.huji.ac.il
Jon KleinbergProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Eli UpfalComputer Science Professor, Brown UniversityVerified email at brown.edu
Ittai AbrahamIntelVerified email at cs.huji.ac.il
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Emin Gün SirerCornell UniversityVerified email at systems.cs.cornell.edu
Dr Bernard WongUniversity of SydneyVerified email at bawtech.com.au
Yishay MansourTel Aviv UniversityVerified email at tauex.tau.ac.il
Ashwinkumar BadanidiyuruGoogle Research Mountain ViewVerified email at google.com
Siddhartha SenMicrosoft Research (NYC)Verified email at microsoft.com
Karthik Abinav SankararamanMeta/Facebook, University of Maryland, College ParkVerified email at fb.com
Chien-Ju HoWashington University in St. LouisVerified email at wustl.edu
Nicole ImmorlicaMicrosoft ResearchVerified email at microsoft.com
Vasilis SyrgkanisAssistant Professor, Stanford UniversityVerified email at stanford.edu
Filip RadlinskiGoogleVerified email at google.com
Omar AlonsoAmazonVerified email at amazon.com
Robert SchapireMicrosoft ResearchVerified email at microsoft.com

Aleksandrs Slivkins

Senior Principal Researcher, Microsoft Research NYC

Verified email at microsoft.com - Homepage

Algorithms machine learning theory algorithmic economics social network analysis


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Introduction to multi-armed bandits A Slivkins Foundations and Trends in Machine Learning 12 (1-2), 1-286, 2019	862	2019
Bandits and experts in metric spaces R Kleinberg, A Slivkins, E Upfal Journal of the ACM (JACM) 66 (4), 30, 2019	589*	2019
Meridian: A lightweight network location service without virtual coordinates B Wong, A Slivkins, EG Sirer ACM SIGCOMM Computer Communication Review 35 (4), 85-96, 2005	588	2005
Contextual bandits with similarity information A Slivkins The Journal of Machine Learning Research 15 (1), 2533-2568, 2014	455	2014
Bandits with knapsacks A Badanidiyuru, R Kleinberg, A Slivkins Journal of the ACM (JACM) 65 (3), 13, 2018	449	2018
The best of both worlds: stochastic and adversarial bandits S Bubeck, A Slivkins Conference on Learning Theory, 42.1-42.23, 2012	232	2012
Triangulation and embedding using small sets of beacons J Kleinberg, A Slivkins, T Wexler Journal of the ACM (JACM) 56 (6), 32, 2009	226*	2009
Dynamic pricing with limited supply M Babaioff, S Dughmi, R Kleinberg, A Slivkins ACM Transactions on Economics and Computation (TEAC) 3 (1), 4, 2015	204	2015
Characterizing truthful multi-armed bandit mechanisms M Babaioff, Y Sharma, A Slivkins SIAM Journal on Computing 43 (1), 194-230, 2014	178*	2014
Incentivizing high quality crowdwork CJ Ho, A Slivkins, S Suri, JW Vaughan Proceedings of the 24th International Conference on World Wide Web, 419-429, 2015	177	2015
One practical algorithm for both stochastic and adversarial bandits Y Seldin, A Slivkins International Conference on Machine Learning, 1287-1295, 2014	166	2014
Ranked bandits in metric spaces: learning diverse rankings over large document collections A Slivkins, F Radlinski, S Gollapudi Journal of Machine Learning Research 14 (Feb), 399-436, 2013	160*	2013
Adapting to a Changing Environment: the Brownian Restless Bandits. A Slivkins, E Upfal COLT, 343-354, 2008	160	2008
Distance estimation and object location via rings of neighbors A Slivkins Distributed Computing 19 (4), 313-333, 2007	141	2007
Bayesian incentive-compatible bandit exploration Y Mansour, A Slivkins, V Syrgkanis Operations Research 68 (4), 1132-1161, 2020	134*	2020
Making contextual decisions with low technical debt A Agarwal, S Bird, M Cozowicz, L Hoang, J Langford, S Lee, J Li, ... arXiv preprint arXiv:1606.03966, 2016	130*	2016
Resourceful contextual bandits A Badanidiyuru, J Langford, A Slivkins Conference on Learning Theory, 1109-1134, 2014	130	2014
Truthful mechanisms with implicit payment computation M Babaioff, RD Kleinberg, A Slivkins Journal of the ACM (JACM) 62 (2), 1-37, 2015	119	2015
Adaptive contract design for crowdsourcing markets: Bandit algorithms for repeated principal-agent problems CJ Ho, A Slivkins, JW Vaughan Journal of Artificial Intelligence Research 55, 317-359, 2016	115	2016
Metric embeddings with relaxed guarantees THH Chan, K Dhamdhere, A Gupta, J Kleinberg, A Slivkins SIAM Journal on Computing 38 (6), 2303-2329, 2009	109*	2009

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