| Hyperband: A novel bandit-based approach to hyperparameter optimization L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar The Journal of Machine Learning Research 18 (1), 6765-6816, 2017 | 730* | 2017 |
| Hyperband: Bandit-based Configuration Evaluation for Hyperparameter Optimization AT Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh ICLR, 2017 | 580* | 2017 |
| Efficient hyperparameter optimization and infinitely many armed bandits A Rostamizadeh, A Talwalkar, G DeSalvo, K Jamieson, L Li | 91 | 2017 |
| Learning with rejection C Cortes, G DeSalvo, M Mohri International Conference on Algorithmic Learning Theory, 67-82, 2016 | 80 | 2016 |
| Boosting with abstention C Cortes, G DeSalvo, M Mohri Advances in Neural Information Processing Systems, 1660-1668, 2016 | 30 | 2016 |
| Precise measurement of laser power using an optomechanical system K Agatsuma, D Friedrich, S Ballmer, G DeSalvo, S Sakata, E Nishida, ... Optics express 22 (2), 2013-2030, 2014 | 18 | 2014 |
| Online learning with abstention C Cortes, G DeSalvo, C Gentile, M Mohri, S Yang international conference on machine learning, 1059-1067, 2018 | 11 | 2018 |
| Region-based active learning C Cortes, G DeSalvo, C Gentile, M Mohri, N Zhang The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 9 | 2019 |
| WWW 2018 L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 8 | 2018 |
| Discrepancy-based algorithms for non-stationary rested bandits C Cortes, G DeSalvo, V Kuznetsov, M Mohri, S Yang arXiv preprint arXiv:1710.10657, 2017 | 8 | 2017 |
| Hyperband: A novel bandit-based approach to hyperparameter optimization. arXiv 2016 L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar arXiv preprint arXiv:1603.06560, 2016 | 7 | 2016 |
| Active learning with disagreement graphs C Cortes, G DeSalvo, M Mohri, N Zhang, C Gentile International Conference on Machine Learning, 1379-1387, 2019 | 6 | 2019 |
| Learning with deep cascades G DeSalvo, M Mohri, U Syed International Conference on Algorithmic Learning Theory, 254-269, 2015 | 6 | 2015 |
| Random Composite Forests. G DeSalvo, M Mohri AAAI, 1540-1546, 2016 | 5 | 2016 |
| Online learning with sleeping experts and feedback graphs C Cortes, G DeSalvo, C Gentile, M Mohri, S Yang International Conference on Machine Learning, 1370-1378, 2019 | 4 | 2019 |
| Multi-armed bandits with non-stationary rewards C Cortes, G DeSalvo, V Kuznetsov, M Mohri, S Yand CoRR, abs/1710.10657 1, 2017 | 4 | 2017 |
| NIPS 2016 L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar, CMCB Trees | 2 | |
| High accuracy measurement of the quantum efficiency using radiation pressure K Agatsuma, T Mori, S Ballmer, G DeSalvo, S Sakata, E Nishida, ... J. Phys. Conf. Ser. 363, 012002, 2012 | 1 | 2012 |
| Understanding the Effects of Batching in Online Active Learning K Amin, C Cortes, G DeSalvo, A Rostamizadeh International Conference on Artificial Intelligence and Statistics, 3482-3492, 2020 | | 2020 |
| Adaptive Region-Based Active Learning C Cortes, G DeSalvo, C Gentile, M Mohri, N Zhang arXiv preprint arXiv:2002.07348, 2020 | | 2020 |
