Matan Schliserman

According to our database, Matan Schliserman authored at least 9 papers between 2022 and 2025.

Collaborative distances:

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

2025

Flat Minima and Generalization: Insights from Stochastic Convex Optimization.

Matan Schliserman, Shira Vansover-Hager, Tomer Koren

CoRR, November, 2025

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime.

Amit Attia, Matan Schliserman, Uri Sherman, Tomer Koren

CoRR, July, 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, June, 2025

Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification.

Matan Schliserman, Tomer Koren

CoRR, May, 2025

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, April, 2025

The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization.

Matan Schliserman, Uri Sherman, Tomer Koren

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024

Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization.

Matan Schliserman, Tomer Koren

CoRR, 2024

2023

Tight Risk Bounds for Gradient Descent on Separable Data.

Matan Schliserman, Tomer Koren

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

2022

Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond.

Matan Schliserman, Tomer Koren

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022