| Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes AL Sanborn, SSP Rao, SC Huang, NC Durand, MH Huntley, AI Jewett, ... Proceedings of the National Academy of Sciences 112 (47), E6456-E6465, 2015 | 1338 | 2015 |
| Momentum-based variance reduction in non-convex sgd A Cutkosky, F Orabona Advances in neural information processing systems 32, 2019 | 160 | 2019 |
| Black-box reductions for parameter-free online learning in banach spaces A Cutkosky, F Orabona Conference On Learning Theory, 1493-1529, 2018 | 80 | 2018 |
| Online learning without prior information A Cutkosky, K Boahen arXiv preprint arXiv:1703.02629, 2017 | 55 | 2017 |
| Momentum improves normalized sgd A Cutkosky, H Mehta International conference on machine learning, 2260-2268, 2020 | 39 | 2020 |
| Anytime online-to-batch, optimism and acceleration A Cutkosky International Conference on Machine Learning, 1446-1454, 2019 | 28* | 2019 |
| Online learning with imperfect hints A Bhaskara, A Cutkosky, R Kumar, M Purohit International Conference on Machine Learning, 822-831, 2020 | 27 | 2020 |
| Parameter-free, dynamic, and strongly-adaptive online learning A Cutkosky International Conference on Machine Learning, 2250-2259, 2020 | 23 | 2020 |
| Online convex optimization with unconstrained domains and losses A Cutkosky, KA Boahen Advances in Neural Information Processing Systems 29, 2016 | 23 | 2016 |
| Matrix-free preconditioning in online learning A Cutkosky, T Sarlos International Conference on Machine Learning, 1455-1464, 2019 | 18 | 2019 |
| Distributed stochastic optimization via adaptive SGD A Cutkosky, R Busa-Fekete Advances in Neural Information Processing Systems 31, 2018 | 16 | 2018 |
| Dynamic balancing for model selection in bandits and rl A Cutkosky, C Dann, A Das, C Gentile, A Pacchiano, M Purohit International Conference on Machine Learning, 2276-2285, 2021 | 15 | 2021 |
| Artificial constraints and hints for unbounded online learning A Cutkosky Conference on Learning Theory, 874-894, 2019 | 15 | 2019 |
| Combining online learning guarantees A Cutkosky Conference on Learning Theory, 895-913, 2019 | 12 | 2019 |
| Kernel truncated randomized ridge regression: Optimal rates and low noise acceleration KS Jun, A Cutkosky, F Orabona Advances in neural information processing systems 32, 2019 | 11 | 2019 |
| Stochastic and adversarial online learning without hyperparameters A Cutkosky, KA Boahen Advances in Neural Information Processing Systems 30, 2017 | 11 | 2017 |
| Extreme memorization via scale of initialization H Mehta, A Cutkosky, B Neyshabur arXiv preprint arXiv:2008.13363, 2020 | 10 | 2020 |
| Online linear optimization with many hints A Bhaskara, A Cutkosky, R Kumar, M Purohit Advances in neural information processing systems 33, 9530-9539, 2020 | 9 | 2020 |
| Adversarial tracking control via strongly adaptive online learning with memory Z Zhang, A Cutkosky, I Paschalidis International Conference on Artificial Intelligence and Statistics, 8458-8492, 2022 | 5 | 2022 |
| High-probability bounds for non-convex stochastic optimization with heavy tails A Cutkosky, H Mehta Advances in Neural Information Processing Systems 34, 4883-4895, 2021 | 5 | 2021 |
Francesco OrabonaAssociate Professor, Boston UniversityVerified email at orabona.com
