Agnostic Sample Compression for Linear Regression. - Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (CoRR, 2018)

Sample Compression for Real-Valued Learners. - Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (ALT, 2019)

On the Sample Complexity of Privately Learning Axis-Aligned Rectangles. - Menachem Sadigurschi; Uri Stemmer (NeurIPS, 2021)

Adaptive Data Analysis with Correlated Observations. - Aryeh Kontorovich; Menachem Sadigurschi; Uri Stemmer (ICML, 2022)

Differentially-Private Bayes Consistency. - Olivier Bousquet; Haim Kaplan; Aryeh Kontorovich; Yishay Mansour; Shay Moran; Menachem Sadigurschi; Uri Stemmer (CoRR, 2022)

Relaxed Models for Adversarial Streaming: The Bounded Interruptions Model and the Advice Model. - Menachem Sadigurschi; Moshe Shechner; Uri Stemmer (ESA, 2023)

Relaxed Models for Adversarial Streaming: The Advice Model and the Bounded Interruptions Model. - Menachem Sadigurschi; Moshe Shechner; Uri Stemmer (CoRR, 2023)

Agnostic Sample Compression Schemes for Regression. - Idan Attias; Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (ICML, 2024)