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Lucas Rosenblatt
Lucas Rosenblatt
Phd Candidate, NYU
Verified email at nyu.edu - Homepage
Title
Cited by
Cited by
Year
Differentially Private Synthetic Data: Applied Evaluations and Enhancements
L Rosenblatt, X Liu, S Pouyanfar, E de Leon, A Desai, J Allen
arXiv preprint arXiv:2011.05537, 2020
582020
Vocal programming for people with upper-body motor impairments
L Rosenblatt, P Carrington, K Hara, JP Bigham
Proceedings of the 15th International Web for All Conference, 1-10, 2018
292018
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
A Bell, L Bynum, N Drushchak, T Herasymova, L Rosenblatt, ...
Proceedings of ACM Conference on Fairness, Accountability, and Transparency …, 2023
122023
Vocalide: An ide for programming via speech recognition
L Rosenblatt
Proceedings of the 19th International ACM SIGACCESS Conference on Computers …, 2017
102017
Counterfactual Fairness Is Basically Demographic Parity
L Rosenblatt, RT Witter
AAAI Conference on Artificial Intelligence 2023 (37), 2022
92022
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy
L Rosenblatt, A Holovenko, T Rumezhak, A Stadnik, B Herman, ...
Proceedings of the VLDB Endowment 17, 2022
62022
Spending Privacy Budget Fairly and Wisely
L Rosenblatt, J Allen, J Stoyanovich
ICML Workshop on the Theory and Practice of Differential Privacy (TPDP 2022), 2022
52022
Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI
L Rosenblatt, L Piedras, J Wilkins
Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI), 15-24, 2022
32022
PerfGuard: deploying ML-for-systems without performance regressions, almost!
R Ammerlaan, G Antonius, M Friedman, HMS Hossain, A Jindal, ...
Proceedings of the VLDB Endowment 14 (13), 3362-3375, 2021
32021
A simple and practical method for reducing the disparate impact of differential privacy
L Rosenblatt, J Stoyanovich, C Musco
Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21554 …, 2024
12024
PerfGuard: Deploying ML-for-Systems without Performance Regressions
HMS Hossain, L Rosenblatt, G Antonius, I Shaffer, R Ammerlaan, A Roy, ...
Proceedings of Machine Learning and Systems 2020 (MLSys 2020), 2020
12020
Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings
R Wolfe, I Slaughter, B Han, B Wen, Y Yang, L Rosenblatt, B Herman, ...
The 2024 ACM Conference on Fairness, Accountability, and Transparency, 1199-1210, 2024
2024
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy
L Rosenblatt, B Herman, A Holovenko, W Lee, J Loftus, E McKinnie, ...
ACM SIGMOD Record 53 (1), 65-74, 2024
2024
I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives
RT Witter, L Rosenblatt
Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22429 …, 2024
2024
System and method for machine learning for system deployments without performance regressions
IR Shaffer, RHL Ammerlaan, G Antonius, MT Friedman, ROY Abhishek, ...
US Patent App. 18/345,789, 2023
2023
Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology
L Rosenblatt, B Han, E Posthumus, T Crimmins, B Howe
arxiv.org/pdf/2310.00740.pdf, 2023
2023
System and method for machine learning for system deployments without performance regressions
IR Shaffer, RHL Ammerlaan, G Antonius, MT Friedman, ROY Abhishek, ...
US Patent 11,748,350, 2023
2023
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