| Generative and multi-phase learning for computer systems optimization Y Ding, N Mishra, H Hoffmann Proceedings of the 46th International Symposium on Computer Architecture, 39-52, 2019 | 64 | 2019 |
| An adaptive gradient method for online AUC maximization Y Ding, P Zhao, S Hoi, YS Ong Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 54 | 2015 |
| A polynomial-time algorithm for learning nonparametric causal graphs M Gao, Y Ding, B Aragam Advances in Neural Information Processing Systems 33, 11599-11611, 2020 | 47 | 2020 |
| CAFQA: A classical simulation bootstrap for variational quantum algorithms GS Ravi, P Gokhale, Y Ding, W Kirby, K Smith, JM Baker, PJ Love, ... Proceedings of the 28th ACM International Conference on Architectural …, 2022 | 45 | 2022 |
| Multiresolution kernel approximation for Gaussian process regression Y Ding, R Kondor, J Eskreis-Winkler Advances in Neural Information Processing Systems 30, 2017 | 29 | 2017 |
| Neighborhood street activity and greenspace usage uniquely contribute to predicting crime KE Schertz, J Saxon, C Cardenas-Iniguez, LMA Bettencourt, Y Ding, ... Npj Urban Sustainability 1 (1), 19, 2021 | 28 | 2021 |
| Large scale kernel methods for online AUC maximization Y Ding, C Liu, P Zhao, SCH Hoi 2017 IEEE International Conference on Data Mining (ICDM), 91-100, 2017 | 28 | 2017 |
| Generalizable and interpretable learning for configuration extrapolation Y Ding, A Pervaiz, M Carbin, H Hoffmann Proceedings of the 29th ACM joint meeting on European software engineering …, 2021 | 21 | 2021 |
| Minimax designs for causal effects in temporal experiments with treatment habituation GW Basse, Y Ding, P Toulis Biometrika 110 (1), 155-168, 2023 | 19 | 2023 |
| Minimax crossover designs G Basse, Y Ding, P Toulis arXiv preprint arXiv:1908.03531, 2019 | 8 | 2019 |
| NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction Y Ding, A Rao, H Song, R Willett, HH Hoffmann Proceedings of Machine Learning and Systems 4, 190-203, 2022 | 7 | 2022 |
| Programming with neural surrogates of programs A Renda, Y Ding, M Carbin Proceedings of the 2021 ACM SIGPLAN International Symposium on New Ideas …, 2021 | 7 | 2021 |
| Learning relative similarity by stochastic dual coordinate ascent P Wu, Y Ding, P Zhao, C Miao, S Hoi Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 7 | 2014 |
| Uncertainty-Aware Decarbonization for Datacenters A Li, S Liu, Y Ding ACM HotCarbon Workshop on Sustainable Computer Systems, 2024 | 6 | 2024 |
| Cafqa: Clifford ansatz for quantum accuracy GS Ravi, P Gokhale ArXivorg, 2022 | 6 | 2022 |
| The University of Chicago YI DING | 6 | 2018 |
| Sustainable LLM Serving: Environmental Implications, Challenges, and Opportunities Y Ding, T Shi 2024 IEEE 15th International Green and Sustainable Computing Conference …, 2024 | 5 | 2024 |
| Towards sustainable large language model serving S Nguyen, B Zhou, Y Ding, S Liu ACM HotCarbon Workshop on Sustainable Computer Systems, 2024 | 5 | 2024 |
| Adaptive subgradient methods for online AUC maximization Y Ding, P Zhao, SCH Hoi, YS Ong arXiv preprint arXiv:1602.00351, 2016 | 5 | 2016 |
| Cello: Efficient computer systems optimization with predictive early termination and censored regression Y Ding, A Renda, A Pervaiz, M Carbin, H Hoffmann arXiv preprint arXiv:2204.04831, 2022 | 4 | 2022 |
Henry HoffmannLiew Family Chair of Computer Science, University of ChicagoAdresse e-mail validée de cs.uchicago.edu
