Jessica Sorrell

According to our database, Jessica Sorrell authored at least 18 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2026

Model Agreement via Anchoring.

Eric Eaton, Surbhi Goel, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

CoRR, February, 2026

Computationally Efficient Replicable Learning of Parities.

Moshe Noivirt, Jessica Sorrell, Eliad Tsfadia

CoRR, February, 2026

The Cost of Replicability in Active Learning.

Rupkatha Hira, Dominik Kau, Jessica Sorrell

Trans. Mach. Learn. Res., 2026

2025

Replicable Reinforcement Learning with Linear Function Approximation.

Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

CoRR, September, 2025

Sensitivity of Stability: Theoretical & Empirical Analysis of Replicability for Adaptive Data Selection in Transfer Learning.

Prabhav Singh, Jessica Sorrell

CoRR, August, 2025

Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces.

Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Oracle-Efficient Reinforcement Learning for Max Value Ensembles.

Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Stability Is Stable: Connections between Replicability, Privacy, and Adaptive Generalization.

Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Replicable Reinforcement Learning.

Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multicalibration as Boosting for Regression.

Ira Globus-Harris, Declan Harrison, Michael Kearns, Aaron Roth, Jessica Sorrell

Proceedings of the International Conference on Machine Learning, 2023

2022

Algorithmic Stability for Responsible Computing

Jessica Sorrell

PhD thesis, 2022

Reproducibility in learning.

Russell Impagliazzo, Rex Lei, Toniann Pitassi, Jessica Sorrell

Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Securing Approximate Homomorphic Encryption Using Differential Privacy.

Baiyu Li, Daniele Micciancio, Mark Schultz, Jessica Sorrell

Proceedings of the Advances in Cryptology - CRYPTO 2022, 2022

2021

Boosting in the Presence of Massart Noise.

Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos

Proceedings of the Conference on Learning Theory, 2021

2020

Efficient, Noise-Tolerant, and Private Learning via Boosting.

Mark Bun, Marco Leandro Carmosino, Jessica Sorrell

Proceedings of the Conference on Learning Theory, 2020

Simpler Statistically Sender Private Oblivious Transfer from Ideals of Cyclotomic Integers.

Daniele Micciancio, Jessica Sorrell

Proceedings of the Advances in Cryptology - ASIACRYPT 2020, 2020

2018

The Fiat-Shamir Zoo: Relating the Security of Different Signature Variants.

Matilda Backendal, Mihir Bellare, Jessica Sorrell, Jiahao Sun

Proceedings of the Secure IT Systems - 23rd Nordic Conference, NordSec 2018, Oslo, Norway, 2018

Ring Packing and Amortized FHEW Bootstrapping.

Daniele Micciancio, Jessica Sorrell

Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018