Matan Schliserman

According to our database1, Matan Schliserman authored at least 8 papers between 2022 and 2025.

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Bibliography

2025
Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime.
CoRR, July, 2025

Optimal Rates in Continual Linear Regression via Increasing Regularization.
CoRR, June, 2025

Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification.
CoRR, May, 2025

Better Rates for Random Task Orderings in Continual Linear Models.
CoRR, April, 2025

The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization.
Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization.
CoRR, 2024

2023
Tight Risk Bounds for Gradient Descent on Separable Data.
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.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022


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