Convergence of Stochastic Gradient Descent Schemes for Lojasiewicz-Landscapes S Dereich, S Kassing Journal of Machine Learning 3 (3), 245--281, 2024 | 34 | 2024 |
On minimal representations of shallow ReLU networks S Dereich, S Kassing Neural Networks 148, 121-128, 2022 | 15 | 2022 |
Stochastic modified flows, mean-field limits and dynamics of stochastic gradient descent B Gess, S Kassing, V Konarovskyi Journal of Machine Learning Research 25 (30), 1-27, 2024 | 9 | 2024 |
Central limit theorems for stochastic gradient descent with averaging for stable manifolds S Dereich, S Kassing Electronic Journal of Probability 28, 1-48, 2023 | 9* | 2023 |
Cooling down stochastic differential equations: Almost sure convergence S Dereich, S Kassing Stochastic Processes and their Applications 152, 289-311, 2022 | 9 | 2022 |
On the existence of minimizers in shallow residual ReLU neural network optimization landscapes S Dereich, A Jentzen, S Kassing arXiv preprint arXiv:2302.14690, 2023 | 6 | 2023 |
Convergence rates for momentum stochastic gradient descent with noise of machine learning type B Gess, S Kassing arXiv preprint arXiv:2302.03550, 2023 | 5 | 2023 |
On the Existence of Optimal Shallow Feedforward Networks with ReLU Activation S Dereich, S Kassing Journal of Machine Learning 3 (1), 1-22, 2024 | 4 | 2024 |
Stochastic Modified Flows for Riemannian Stochastic Gradient Descent B Gess, S Kassing, N Rana arXiv preprint arXiv:2402.03467, 2024 | | 2024 |
Stochastic Approximation with a Focus on Machine Learning Applications S Kassing Westfälische Wilhelms-Universität Münster, 2021 | | 2021 |