| Online learning for time series prediction O Anava, E Hazan, S Mannor, O Shamir Conference on learning theory, 172-184, 2013 | 178 | 2013 |
| k*-nearest neighbors: From global to local O Anava, K Levy Advances in neural information processing systems 29, 2016 | 114 | 2016 |
| Online time series prediction with missing data O Anava, E Hazan, A Zeevi International conference on machine learning, 2191-2199, 2015 | 96 | 2015 |
| Online learning for adversaries with memory: price of past mistakes O Anava, E Hazan, S Mannor Advances in Neural Information Processing Systems, 784-792, 2015 | 91 | 2015 |
| Multi-armed Bandits: Competing with Optimal Sequences ZS Karnin, O Anava Advances in Neural Information Processing Systems, 199-207, 2016 | 65 | 2016 |
| Excuseme: Asking users to help in item cold-start recommendations M Aharon, O Anava, N Avigdor-Elgrabli, D Drachsler-Cohen, S Golan, ... Proceedings of the 9th ACM Conference on Recommender Systems, 83-90, 2015 | 42 | 2015 |
| Budget-constrained item cold-start handling in collaborative filtering recommenders via optimal design O Anava, S Golan, N Golbandi, Z Karnin, R Lempel, O Rokhlenko, ... Proceedings of the 24th international conference on world wide web, 45-54, 2015 | 35 | 2015 |
| Method and system for cold-start item recommendation OS Somekh, S Golan, N Golbandi, Z Karnin, O Rokhlenko, O Anava, ... US Patent 10,699,198, 2020 | 9 | 2020 |
| Heteroscedastic sequences: beyond gaussianity O Anava, S Mannor International Conference on Machine Learning, 755-763, 2016 | 8 | 2016 |
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at princeton.edu
