Efficient Loss-Based Decoding on Graphs for Extreme Classification. - Itay Evron; Edward Moroshko; Koby Crammer (NeurIPS, 2018)

How do infinite width bounded norm networks look in function space? - Pedro Savarese; Itay Evron; Daniel Soudry; Nathan Srebro (COLT, 2019)

Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks. - Yochai Zur; Chaim Baskin; Evgenii Zheltonozhskii; Brian Chmiel; Itay Evron; Alexander M. Bronstein; Avi Mendelson (CoRR, 2019)

How catastrophic can catastrophic forgetting be in linear regression? - Itay Evron; Edward Moroshko; Rachel A. Ward; Nathan Srebro; Daniel Soudry (COLT, 2022)

The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study. - Itay Evron; Ophir Onn; Tamar Weiss Orzech; Hai Azeroual; Daniel Soudry (AISTATS, 2023)

Continual Learning in Linear Classification on Separable Data. - Itay Evron; Edward Moroshko; Gon Buzaglo; Maroun Khriesh; Badea Marjieh; Nathan Srebro; Daniel Soudry (ICML, 2023)

The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model. - Daniel Goldfarb; Itay Evron; Nir Weinberger; Daniel Soudry; Paul Hand (ICLR, 2024)

Provable Tempered Overfitting of Minimal Nets and Typical Nets. - Itamar Harel; William Hoza; Gal Vardi; Itay Evron; Nati Srebro; Daniel Soudry (NeurIPS, 2024)

Better Rates for Random Task Orderings in Continual Linear Models. - Itay Evron; Ran Levinstein; Matan Schliserman; Uri Sherman; Tomer Koren; Daniel Soudry; Nathan Srebro (CoRR, 2025)

Optimal Rates in Continual Linear Regression via Increasing Regularization. - Ran Levinstein; Amit Attia; Matan Schliserman; Uri Sherman; Tomer Koren; Daniel Soudry; Itay Evron (CoRR, 2025)