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Giuseppe Vietri
Giuseppe Vietri
Applied Scientist, AWS
Verified email at amazon.com - Homepage
Title
Cited by
Cited by
Year
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
1222018
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
842020
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
642021
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
582021
Private reinforcement learning with pac and regret guarantees
G Vietri, B Balle, A Krishnamurthy, S Wu
International Conference on Machine Learning, 9754-9764, 2020
522020
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
262023
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
212022
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
192013
Oracle efficient private non-convex optimization
S Neel, A Roth, G Vietri, S Wu
International conference on machine learning, 7243-7252, 2020
132020
Generating private synthetic data with genetic algorithms
T Liu, J Tang, G Vietri, S Wu
International Conference on Machine Learning, 22009-22027, 2023
112023
Differentially private objective perturbation: Beyond smoothness and convexity
S Neel, A Roth, G Vietri, ZS Wu
arXiv preprint arXiv:1909.01783, 2019
72019
Improved regret for differentially private exploration in linear mdp
DDT Ngo, G Vietri, S Wu
International Conference on Machine Learning, 16529-16552, 2022
62022
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
52018
Analyzing adaptive cache replacement strategies
ME Consuegra, WA Martinez, G Narasimhan, R Rangaswami, L Shao, ...
arXiv preprint arXiv:1503.07624, 2015
42015
Systems and methods for managing cache replacement with machine learning
G Narasimhan, G Vietri, WA Martinez
US Patent 10,558,583, 2020
32020
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
12023
Generating Differentially Private Synthetic Data
G Vietri
University of Minnesota, 2023
12023
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
12020
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
Cache Replacement as a MAB with Delayed Feedback and Decaying Costs
F Beente Yusuf, V Stebliankin, G Vietri, G Narasimhan
arXiv e-prints, arXiv: 2009.11330, 2020
2020
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Articles 1–20