Ellen Vitercik

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Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Travis DickUniversity of PennsylvaniaVerified email at seas.upenn.edu
Colin WhiteAbacus.AIVerified email at cs.cmu.edu
Vaishnavh NagarajanCarnegie Mellon UniversityVerified email at cs.cmu.edu
Bernhard HaeuplerAssociate Professor, CMUVerified email at cs.cmu.edu
Amirbehshad ShahrasbiHarvard UniversityVerified email at seas.harvard.edu
Adam Tauman KalaiMicrosoft ResearchVerified email at microsoft.com
Carl KingsfordProfessor, Computational Biology Department, School of Computer Science, CarnegieVerified email at cs.cmu.edu
Cameron MuscoAssistant Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Daniel AlabiHarvard UniversityVerified email at g.harvard.edu
Katrina LigettHebrew UniversityVerified email at mail.huji.ac.il
Christos TzamosUniversity of Wisconsin-MadisonVerified email at wisc.edu
Dan DeBlasioAssistant Professor, Computer Science, University of Texas at El PasoVerified email at utep.edu
Nika HaghtalabUniversity of California, BerkeleyVerified email at berkeley.edu
Jennifer ChayesTechnical Fellow & Managing Director, MicrosoftVerified email at microsoft.com
andres muñoz medinaGoogle ResearchVerified email at google.com
Umar SyedResearch Scientist, GoogleVerified email at google.com
Sergei VassilvitskiiGoogleVerified email at google.com

Ellen Vitercik

Carnegie Mellon University

Verified email at cs.cmu.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning to branch MF Balcan, T Dick, T Sandholm, E Vitercik International conference on machine learning, 344-353, 2018	86	2018
A General Theory of Sample Complexity for Multi-Item Profit Maximization MF Balcan, T Sandholm, E Vitercik Proceedings of the 2018 ACM Conference on Economics and Computation, 173-174, 2018	51	2018
Sample Complexity of Automated Mechanism Design MF Balcan, T Sandholm, E Vitercik Advances In Neural Information Processing Systems, 2083-2091, 2016	44	2016
Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions B Haeupler, A Shahrasbi, E Vitercik arXiv preprint arXiv:1707.04233, 2017	41	2017
Dispersion for data-driven algorithm design, online learning, and private optimization MF Balcan, T Dick, E Vitercik 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS …, 2018	37	2018
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems MF Balcan, V Nagarajan, E Vitercik, C White Conference on Learning Theory, 213-274, 2017	36	2017
Learning combinatorial functions from pairwise comparisons MF Balcan, E Vitercik, C White Conference on Learning Theory, 310-335, 2016	18	2016
Estimating Approximate Incentive Compatibility E Vitercik, MF Balcan, T Sandholm ACM Conference on Economics and Computation, 2019	15*	2019
Learning to prune: Speeding up repeated computations D Alabi, AT Kalai, K Liggett, C Musco, C Tzamos, E Vitercik Conference on Learning Theory, 30-33, 2019	11	2019
How much data is sufficient to learn high-performing algorithms? MF Balcan, D DeBlasio, T Dick, C Kingsford, T Sandholm, E Vitercik arXiv preprint arXiv:1908.02894, 2019	10	2019
Learning to optimize computational resources: Frugal training with generalization guarantees MF Balcan, T Sandholm, E Vitercik Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3227-3234, 2020	6	2020
Refined bounds for algorithm configuration: The knife-edge of dual class approximability MF Balcan, T Sandholm, E Vitercik International Conference on Machine Learning, 580-590, 2020	3	2020
Algorithmic greenlining: An approach to increase diversity C Borgs, J Chayes, N Haghtalab, AT Kalai, E Vitercik Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 69-76, 2019	2	2019
How much data is sufficient to learn high-performing algorithms? generalization guarantees for data-driven algorithm design MF Balcan, D DeBlasio, T Dick, C Kingsford, T Sandholm, E Vitercik Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021	1	2021
Generalization in portfolio-based algorithm selection MF Balcan, T Sandholm, E Vitercik arXiv preprint arXiv:2012.13315, 2020	1	2020
Generalization Guarantees for Multi-item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms MF Balcan, T Sandholm, E Vitercik arXiv preprint arXiv:1705.00243, 2017	1	2017
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond MF Balcan, S Prasad, T Sandholm, E Vitercik arXiv preprint arXiv:2106.04033, 2021		2021
Private optimization without constraint violations A Muñoz Medina, U Syed, S Vassilvtiskii, E Vitercik International Conference on Artificial Intelligence and Statistics, 2557-2565, 2021		2021

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