Sebastian Kassing

According to our database, Sebastian Kassing authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

The Role of Target Update Frequencies in Q-Learning.

Simon Weissmann, Tilman Aach, Benedikt Wille, Sebastian Kassing, Leif Döring

CoRR, February, 2026

An Approximate Ascent Approach To Prove Convergence of PPO.

Leif Döring, Daniel Schmidt, Moritz Melcher, Sebastian Kassing, Benedikt Wille, Tilman Aach, Simon Weissmann

CoRR, February, 2026

2025

ODE approximation for the Adam algorithm: General and overparametrized setting.

Steffen Dereich, Arnulf Jentzen, Sebastian Kassing

CoRR, November, 2025

Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization.

Sebastian Kassing, Simon Weissmann, Leif Döring

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

On the Existence of Minimizers in Shallow Residual ReLU Neural Network Optimization Landscapes.

Steffen Dereich, Arnulf Jentzen, Sebastian Kassing

SIAM J. Numer. Anal., 2024

Stochastic Modified Flows for Riemannian Stochastic Gradient Descent.

Benjamin Gess, Sebastian Kassing, Nimit Rana

SIAM J. Control. Optim., 2024

Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent.

Benjamin Gess, Sebastian Kassing, Vitalii Konarovskyi

J. Mach. Learn. Res., 2024

Polyak's Heavy Ball Method Achieves Accelerated Local Rate of Convergence under Polyak-Lojasiewicz Inequality.

Sebastian Kassing, Simon Weissmann

CoRR, 2024

2023

On the existence of optimal shallow feedforward networks with ReLU activation.

Steffen Dereich, Sebastian Kassing

CoRR, 2023

Convergence rates for momentum stochastic gradient descent with noise of machine learning type.

Benjamin Gess, Sebastian Kassing

CoRR, 2023

2022

On minimal representations of shallow ReLU networks.

Steffen Dereich, Sebastian Kassing

Neural Networks, 2022

2021

Stochastic approximation with a focus on machine learning applications.

Sebastian Kassing

PhD thesis, 2021

Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes.

Steffen Dereich, Sebastian Kassing

CoRR, 2021