Algorithmic Instabilities of Accelerated Gradient Descent. - Amit Attia; Tomer Koren (NeurIPS, 2021)

The Instability of Accelerated Gradient Descent. - Amit Attia; Tomer Koren (CoRR, 2021)

Uniform Stability for First-Order Empirical Risk Minimization. - Amit Attia; Tomer Koren (COLT, 2022)

SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance. - Amit Attia; Tomer Koren (ICML, 2023)

How Free is Parameter-Free Stochastic Optimization? - Amit Attia; Tomer Koren (ICML, 2024)

A Note on High-Probability Analysis of Algorithms with Exponential, Sub-Gaussian, and General Light Tails. - Amit Attia; Tomer Koren (CoRR, 2024)

Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching. - Amit Attia; Ofir Gaash; Tomer Koren (CoRR, 2024)

Benefits of Learning Rate Annealing for Tuning-Robustness in Stochastic Optimization. - Amit Attia; Tomer Koren (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)

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime. - Amit Attia; Matan Schliserman; Uri Sherman; Tomer Koren (CoRR, 2025)