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Jessica Sorrell
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2020 – today
- 2024
- [i11]Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell:
Oracle-Efficient Reinforcement Learning for Max Value Ensembles. CoRR abs/2405.16739 (2024) - 2023
- [c10]Ira Globus-Harris, Declan Harrison, Michael Kearns, Aaron Roth, Jessica Sorrell:
Multicalibration as Boosting for Regression. ICML 2023: 11459-11492 - [c9]Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell:
Replicable Reinforcement Learning. NeurIPS 2023 - [c8]Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell:
Stability Is Stable: Connections between Replicability, Privacy, and Adaptive Generalization. STOC 2023: 520-527 - [i10]Ira Globus-Harris, Declan Harrison, Michael Kearns, Aaron Roth, Jessica Sorrell:
Multicalibration as Boosting for Regression. CoRR abs/2301.13767 (2023) - [i9]Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell:
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization. CoRR abs/2303.12921 (2023) - [i8]Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell:
Replicable Reinforcement Learning. CoRR abs/2305.15284 (2023) - 2022
- [b1]Jessica Sorrell:
Algorithmic Stability for Responsible Computing. University of California, San Diego, USA, 2022 - [c7]Baiyu Li, Daniele Micciancio, Mark Schultz, Jessica Sorrell:
Securing Approximate Homomorphic Encryption Using Differential Privacy. CRYPTO (1) 2022: 560-589 - [c6]Russell Impagliazzo, Rex Lei, Toniann Pitassi, Jessica Sorrell:
Reproducibility in learning. STOC 2022: 818-831 - [i7]Russell Impagliazzo, Rex Lei, Toniann Pitassi, Jessica Sorrell:
Reproducibility in Learning. CoRR abs/2201.08430 (2022) - [i6]Baiyu Li, Daniele Micciancio, Mark Schultz, Jessica Sorrell:
Securing Approximate Homomorphic Encryption Using Differential Privacy. IACR Cryptol. ePrint Arch. 2022: 816 (2022) - 2021
- [c5]Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos:
Boosting in the Presence of Massart Noise. COLT 2021: 1585-1644 - [i5]Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos:
Boosting in the Presence of Massart Noise. CoRR abs/2106.07779 (2021) - 2020
- [c4]Daniele Micciancio, Jessica Sorrell:
Simpler Statistically Sender Private Oblivious Transfer from Ideals of Cyclotomic Integers. ASIACRYPT (2) 2020: 381-407 - [c3]Mark Bun, Marco Leandro Carmosino, Jessica Sorrell:
Efficient, Noise-Tolerant, and Private Learning via Boosting. COLT 2020: 1031-1077 - [i4]Mark Bun, Marco Leandro Carmosino, Jessica Sorrell:
Efficient, Noise-Tolerant, and Private Learning via Boosting. CoRR abs/2002.01100 (2020) - [i3]Daniele Micciancio, Jessica Sorrell:
Simpler Statistically Sender Private Oblivious Transfer from Ideals of Cyclotomic Integers. IACR Cryptol. ePrint Arch. 2020: 1413 (2020)
2010 – 2019
- 2018
- [c2]Daniele Micciancio, Jessica Sorrell:
Ring Packing and Amortized FHEW Bootstrapping. ICALP 2018: 100:1-100:14 - [c1]Matilda Backendal, Mihir Bellare, Jessica Sorrell, Jiahao Sun:
The Fiat-Shamir Zoo: Relating the Security of Different Signature Variants. NordSec 2018: 154-170 - [i2]Daniele Micciancio, Jessica Sorrell:
Ring packing and amortized FHEW bootstrapping. IACR Cryptol. ePrint Arch. 2018: 532 (2018) - [i1]Matilda Backendal, Mihir Bellare, Jessica Sorrell, Jiahao Sun:
The Fiat-Shamir Zoo: Relating the Security of Different Signature Variants. IACR Cryptol. ePrint Arch. 2018: 775 (2018)
Coauthor Index
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