Lev Reyzin
Lev Reyzin
Professor of Mathematics, Statistics, and Computer Science; University of Illinois at Chicago
Verified email at - Homepage
Cited by
Cited by
Contextual bandits with linear payoff functions
W Chu, L Li, L Reyzin, RE Schapire
International Conference on Artificial Intelligence and Statistics, 2011
Efficient optimal learning for contextual bandits
M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang
Conference on Uncertainty in Artificial Intelligence, 2011
Contextual bandit algorithms with supervised learning guarantees
A Beygelzimer, J Langford, L Li, L Reyzin, RE Schapire
International Conference on Artificial Intelligence and Statistics, 2011
How boosting the margin can also boost classifier complexity
L Reyzin, RE Schapire
International Conference on Machine Learning, 753-760, 2006
Statistical algorithms and a lower bound for detecting planted cliques
V Feldman, E Grigorescu, L Reyzin, SS Vempala, Y Xiao
Journal of the ACM 64 (2), 8, 2017
Non-stochastic bandit slate problems
S Kale, L Reyzin, RE Schapire
Neural Information Processing Systems, 1054-1062, 2010
Network construction with subgraph connectivity constraints
D Angluin, J Aspnes, L Reyzin
Journal of Combinatorial Optimization 29 (2), 418–432, 2015
Learning and verifying graphs using queries with a focus on edge counting
L Reyzin, N Srivastava
International Conference on Algorithmic Learning Theory, 285-297, 2007
Data stability in clustering: a closer look
S Ben-David, L Reyzin
Theoretical Computer Science 558, 51–61, 2014
Anti-coordination games and stable graph colorings
J Kun, B Powers, L Reyzin
Symposium on Algorithmic Game Theory, 122-133, 2013
On the longest path algorithm for reconstructing trees from distance matrices
L Reyzin, N Srivastava
Information processing letters 101 (3), 98-100, 2007
Boosting on a budget: sampling for feature-efficient prediction
L Reyzin
International Conference on Machine Learning, 2011
On the computational complexity of MapReduce
B Fish, J Kun, ÁD Lelkes, L Reyzin, G Turán
Symposium on Distributed Computing, 2015
On noise-tolerant learning of sparse parities and related problems
E Grigorescu, L Reyzin, S Vempala
International Conference on Algorithmic Learning Theory, 413-424, 2011
Shift-pessimistic active learning using robust bias-aware prediction
A Liu, L Reyzin, BD Ziebart
AAAI Conference on Artificial Intelligence, 2015
Statistical queries and statistical algorithms: foundations and applications
L Reyzin
arXiv preprint arXiv:2004.00557, 2020
Unprovability comes to machine learning
L Reyzin
Nature 565 (7738), 166-167, 2019
On the complexity of learning a class ratio from unlabeled data
B Fish, L Reyzin
Journal of Artificial Intelligence Research 69, 1333–1349-1333–1349, 2020
Learning large-alphabet and analog circuits with value injection queries
D Angluin, J Aspnes, J Chen, L Reyzin
Conference on Learning Theory, 51-65, 2007
Improved algorithms for distributed boosting
J Cooper, L Reyzin
Allerton Conference on Communication, Control, and Computing, 2017
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