| Cascading Bandits: Learning to Rank in the Cascade Model B Kveton, C Szepesvari, Z Wen, A Ashkan 32nd International Conference on Machine Learning, 2015 | 288 | 2015 |
| Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits B Kveton, Z Wen, A Ashkan, C Szepesvari 18th International Conference on Artificial Intelligence and Statistics, 2015 | 281 | 2015 |
| Efficient Thompson Sampling for Online Matrix-Factorization Recommendation J Kawale, H Bui, B Kveton, L Tran-Thanh, S Chawla Advances in Neural Information Processing Systems 28, 1297-1305, 2015 | 200 | 2015 |
| 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, 3022-3032, 2017 | 131* | 2017 |
| User Identification and Personalized Vehicle Settings Management System VB Lortz, B Kveton, VS Kesavan, S Rathi, AP Rangarajan US Patent 9,862,352, 2018 | 126 | 2018 |
| Cascading Bandits for Large-Scale Recommendation Problems S Zong, H Ni, K Sung, NR Ke, Z Wen, B Kveton 32nd Conference on Uncertainty in Artificial Intelligence, 2016 | 117 | 2016 |
| Spectral Bandits for Smooth Graph Functions M Valko, R Munos, B Kveton, T Kocák 31st International Conference on Machine Learning, 2014 | 116 | 2014 |
| Matroid Bandits: Fast Combinatorial Optimization with Learning B Kveton, Z Wen, A Ashkan, H Eydgahi, B Eriksson 30th Conference on Uncertainty in Artificial Intelligence, 2014 | 116 | 2014 |
| Combinatorial Cascading Bandits B Kveton, Z Wen, A Ashkan, C Szepesvari Advances in Neural Information Processing Systems 28, 1450-1458, 2015 | 115 | 2015 |
| Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit Y Cao, Z Wen, B Kveton, Y Xie 22nd International Conference on Artificial Intelligence and Statistics, 418-427, 2019 | 109* | 2019 |
| Leveraging Side Observations in Stochastic Bandits S Caron, B Kveton, M Lelarge, S Bhagat 28th Conference on Uncertainty in Artificial Intelligence, 2012 | 105 | 2012 |
| Efficient Learning in Large-Scale Combinatorial Semi-Bandits Z Wen, B Kveton, A Ashkan 32nd International Conference on Machine Learning, 1113–1122, 2015 | 103 | 2015 |
| Optimal Greedy Diversity for Recommendation A Ashkan, B Kveton, S Berkovsky, Z Wen 24th International Joint Conference on Artificial Intelligence, 1742-1748, 2015 | 97 | 2015 |
| Online Learning to Rank in Stochastic Click Models M Zoghi, T Tunys, M Ghavamzadeh, B Kveton, C Szepesvari, Z Wen 34th International Conference on Machine Learning, 4199-4208, 2017 | 96 | 2017 |
| Solving Factored MDPs with Continuous and Discrete Variables C Guestrin, M Hauskrecht, B Kveton 20th Conference on Uncertainty in Artificial Intelligence, 235-242, 2004 | 96* | 2004 |
| When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions D Dash, B Kveton, JM Agosta, E Schooler, J Chandrashekar, A Bachrach, ... 21st National Conference on Artificial Intelligence, 1115-1122, 2006 | 94 | 2006 |
| DCM Bandits: Learning to Rank with Multiple Clicks S Katariya, B Kveton, C Szepesvari, Z Wen 33rd International Conference on Machine Learning, 2016 | 83 | 2016 |
| Managing your private and public data: Bringing down inference attacks against your privacy S Salamatian, A Zhang, F du Pin Calmon, S Bhamidipati, N Fawaz, ... IEEE Journal of Selected Topics in Signal Processing 9 (7), 1240-1255, 2015 | 77 | 2015 |
| Linear Program Approximations for Factored Continuous-State Markov Decision Processes M Hauskrecht, B Kveton Advances in Neural Information Processing Systems 16, 895-902, 2003 | 76 | 2003 |
| How to hide the elephant-or the donkey-in the room: Practical privacy against statistical inference for large data S Salamatian, A Zhang, F du Pin Calmon, S Bhamidipati, N Fawaz, ... 2013 IEEE Global Conference on Signal and Information Processing, 269-272, 2013 | 74 | 2013 |
