| A Tutorial on Thompson Sampling D Russo, B Van Roy, A Kazerouni, I Osband, Z Wen arXiv, https://arxiv.org/pdf/1707.02038.pdf, 0 | 754* | |
| Generalization and exploration via randomized value functions I Osband, B Van Roy, Z Wen International Conference on Machine Learning, 2377-2386, 2016 | 281 | 2016 |
| Cascading bandits: Learning to rank in the cascade model B Kveton, C Szepesvári, Z Wen, A Ashkan ICML, 2015 | 261 | 2015 |
| Optimal demand response using device based reinforcement learning Z Wen, D O'Neill, HR Maei IEEE Transactions on Smart Grid, 2014 | 254 | 2014 |
| Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits B Kveton, Z Wen, A Ashkan, C Szepesvari International Conference on Artificial Intelligence and Statistics (AISTATS …, 2014 | 248 | 2014 |
| Deep Exploration via Randomized Value Functions. I Osband, B Van Roy, DJ Russo, Z Wen J. Mach. Learn. Res. 20 (124), 1-62, 2019 | 227 | 2019 |
| Online influence maximization under independent cascade model with semi-bandit feedback Z Wen, B Kveton, M Valko, S Vaswani Advances in neural information processing systems 30, 2017 | 113* | 2017 |
| Matroid bandits: Fast combinatorial optimization with learning B Kveton, Z Wen, A Ashkan, H Eydgahi, B Eriksson UAI 2014, 2014 | 112 | 2014 |
| Combinatorial cascading bandits B Kveton, Z Wen, A Ashkan, C Szepesvari Advances in Neural Information Processing Systems 28, 2015 | 100 | 2015 |
| Cascading bandits for large-scale recommendation problems S Zong, H Ni, K Sung, NR Ke, Z Wen, B Kveton arXiv preprint arXiv:1603.05359, 2016 | 96 | 2016 |
| Efficient learning in large-scale combinatorial semi-bandits Z Wen, B Kveton, A Ashkan http://jmlr.org/proceedings/papers/v37/wen15.html, 2014 | 94 | 2014 |
| Nearly optimal adaptive procedure with change detection for piecewise-stationary bandit Y Cao, Z Wen, B Kveton, Y Xie The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 93* | 2019 |
| Optimal Greedy Diversity for Recommendation A Ashkan, B Kveton, S Berkovsky, Z Wen | 87 | 2015 |
| Online learning to rank in stochastic click models M Zoghi, T Tunys, M Ghavamzadeh, B Kveton, C Szepesvari, Z Wen International conference on machine learning, 4199-4208, 2017 | 86 | 2017 |
| DCM Bandits: Learning to Rank with Multiple Clicks S Katariya, B Kveton, C Szepesvári, Z Wen arXiv, 2016 | 77 | 2016 |
| Efficient Exploration and Value Function Generalization in Deterministic Systems Z Wen, B Van Roy Advances in Neural Information Processing Systems, 3021--3029, 2013 | 74 | 2013 |
| Stochastic rank-1 bandits S Katariya, B Kveton, C Szepesvari, C Vernade, Z Wen Artificial Intelligence and Statistics, 392-401, 2017 | 62 | 2017 |
| Model-independent online learning for influence maximization S Vaswani, B Kveton, Z Wen, M Ghavamzadeh, LVS Lakshmanan, ... International Conference on Machine Learning, 3530-3539, 2017 | 61* | 2017 |
| Garbage in, reward out: Bootstrapping exploration in multi-armed bandits B Kveton, C Szepesvari, S Vaswani, Z Wen, T Lattimore, M Ghavamzadeh International Conference on Machine Learning, 3601-3610, 2019 | 54 | 2019 |
| Adaptive submodular maximization in bandit setting V Gabillon, B Kveton, Z Wen, B Eriksson, S Muthukrishnan Advances in Neural Information Processing Systems 26, 2013 | 54 | 2013 |
Branislav KvetonAmazonVerified email at amazon.com
