Learners that Leak Little Information. - Raef Bassily; Shay Moran; Ido Nachum; Jonathan Shafer; Amir Yehudayoff (CoRR, 2017)

Learners that Use Little Information. - Raef Bassily; Shay Moran; Ido Nachum; Jonathan Shafer; Amir Yehudayoff (ALT, 2018)

A Direct Sum Result for the Information Complexity of Learning. - Ido Nachum; Jonathan Shafer; Amir Yehudayoff (COLT, 2018)

Interactive Proofs for Verifying Machine Learning. - Shafi Goldwasser; Guy N. Rothblum; Jonathan Shafer; Amir Yehudayoff (Electron. Colloquium Comput. Complex., 2020)

Fine-Grained Distribution-Dependent Learning Curves. - Olivier Bousquet; Steve Hanneke; Shay Moran; Jonathan Shafer; Ilya O. Tolstikhin (COLT, 2023)

PAC Verification of Statistical Algorithms. - Saachi Mutreja; Jonathan Shafer (COLT, 2023)

A Trichotomy for Transductive Online Learning. - Steve Hanneke; Shay Moran; Jonathan Shafer (NeurIPS, 2023)

The Bayesian Stability Zoo. - Shay Moran; Hilla Schefler; Jonathan Shafer (NeurIPS, 2023)

Topics in the Theory of Learning - Jonathan Shafer (2023)

Fantastic Generalization Measures are Nowhere to be Found. - Michael Gastpar; Ido Nachum; Jonathan Shafer; Thomas Weinberger (ICLR, 2024)

Which Algorithms Have Tight Generalization Bounds? - Michael Gastpar; Ido Nachum; Jonathan Shafer; Thomas Weinberger (CoRR, 2024)

Oblivious Defense in ML Models: Backdoor Removal without Detection. - Shafi Goldwasser; Jonathan Shafer; Neekon Vafa; Vinod Vaikuntanathan (STOC, 2025)

Protocols for Verifying Smooth Strategies in Bandits and Games. - Miranda Christ; Daniel Reichman 001; Jonathan Shafer (CoRR, 2025)