| Driving cache replacement with {ML-based}{LeCaR} G Vietri, LV Rodriguez, WA Martinez, S Lyons, J Liu, R Rangaswami, ... 10th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 18), 2018 | 138 | 2018 |
| New oracle-efficient algorithms for private synthetic data release G Vietri, G Tian, M Bun, T Steinke, S Wu International Conference on Machine Learning, 9765-9774, 2020 | 95 | 2020 |
| Leveraging public data for practical private query release T Liu, G Vietri, T Steinke, J Ullman, S Wu International Conference on Machine Learning, 6968-6977, 2021 | 72 | 2021 |
| Iterative methods for private synthetic data: Unifying framework and new methods T Liu, G Vietri, SZ Wu Advances in Neural Information Processing Systems 34, 690-702, 2021 | 68 | 2021 |
| Private reinforcement learning with pac and regret guarantees G Vietri, B Balle, A Krishnamurthy, S Wu International Conference on Machine Learning, 9754-9764, 2020 | 66 | 2020 |
| Confidence-ranked reconstruction of census microdata from published statistics T Dick, C Dwork, M Kearns, T Liu, A Roth, G Vietri, ZS Wu Proceedings of the National Academy of Sciences 120 (8), e2218605120, 2023 | 34 | 2023 |
| Private synthetic data for multitask learning and marginal queries G Vietri, C Archambeau, S Aydore, W Brown, M Kearns, A Roth, A Siva, ... Advances in Neural Information Processing Systems 35, 18282-18295, 2022 | 32 | 2022 |
| Robotic exoskeleton system controlled by kinect and haptic sensors for physical therapy DC Guevara, G Vietri, M Prabakar, JH Kim 2013 29th Southern Biomedical Engineering Conference, 71-72, 2013 | 19 | 2013 |
| Oracle efficient private non-convex optimization S Neel, A Roth, G Vietri, S Wu International conference on machine learning, 7243-7252, 2020 | 17 | 2020 |
| Generating private synthetic data with genetic algorithms T Liu, J Tang, G Vietri, S Wu International Conference on Machine Learning, 22009-22027, 2023 | 16 | 2023 |
| Improved regret for differentially private exploration in linear mdp DDT Ngo, G Vietri, S Wu International Conference on Machine Learning, 16529-16552, 2022 | 10 | 2022 |
| Differentially private objective perturbation: Beyond smoothness and convexity S Neel, A Roth, G Vietri, ZS Wu arXiv preprint arXiv:1909.01783, 2019 | 6 | 2019 |
| Systems for controlling a movable object JH Kim, N Prabakar, SS Iyengar, L Castillo, J Carvajal, E Almario, G Vietri US Patent 9,934,613, 2018 | 5 | 2018 |
| Analyzing adaptive cache replacement strategies ME Consuegra, WA Martinez, G Narasimhan, R Rangaswami, L Shao, ... arXiv preprint arXiv:1503.07624, 2015 | 4 | 2015 |
| Systems and methods for managing cache replacement with machine learning G Narasimhan, G Vietri, WA Martinez US Patent 10,558,583, 2020 | 3 | 2020 |
| Reply to Sanchéz et al.: Multiplicity does not protect privacy T Dick, C Dwork, M Kearns, T Liu, A Roth, G Vietri, ZS Wu Proceedings of the National Academy of Sciences 120 (18), e2304263120, 2023 | 2 | 2023 |
| Generating Differentially Private Synthetic Data G Vietri University of Minnesota, 2023 | 1 | 2023 |
| Cache Replacement as a MAB with Delayed Feedback and Decaying Costs FB Yusuf, V Stebliankin, G Vietri, G Narasimhan arXiv preprint arXiv:2009.11330, 2020 | 1 | 2020 |
| Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation T Leemann, P Petridis, G Vietri, D Manousakas, A Roth, S Aydore arXiv preprint arXiv:2410.03461, 2024 | | 2024 |
| Leveraging Public Data in Practical Private Query Release: A Case Study with ACS Data T Liu, G Vietri, T Steinke, J Ullman, ZS Wu | | 2021 |
