Mattes Mollenhauer

17 papers A* 2A 1Journal 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
Float8@2bits: Entropy Coding Enables Data-Free Model Compression.
CoRR
Patrick Putzky, Martin Genzel, Mattes Mollenhauer, Sebastian Schulze, Thomas Wollmann, Stefan Dietzel
2025 J jnl
Choose Your Model Size: Any Compression by a Single Gradient Descent.
CoRR
Martin Genzel, Patrick Putzky, Pengfei Zhao, Sebastian Schulze, Mattes Mollenhauer, Robert Seidel, Stefan Dietzel, Thomas Wollmann
2025 J jnl
Choose Your Model Size: Any Compression of Large Language Models Without Re-Computation.
Trans. Mach. Learn. Res.
Martin Genzel, Patrick Putzky, Pengfei Zhao, Sebastian Schulze, Mattes Mollenhauer, Robert Seidel, Stefan Dietzel, Thomas Wollmann
2025 J jnl
Regularized least squares learning with heavy-tailed noise is minimax optimal.
CoRR
Mattes Mollenhauer, Nicole Mücke, Dimitri Meunier, Arthur Gretton
2024 A* conf
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms.
NeurIPS
Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li
2024 J jnl
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms.
CoRR
Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li
2024 J jnl
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm.
J. Mach. Learn. Res.
Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2023 J jnl
Optimal Reaction Coordinates: Variational Characterization and Sparse Computation.
Multiscale Model. Simul.
Andreas Bittracher, Mattes Mollenhauer, Péter Koltai, Christof Schütte
2023 J jnl
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm.
CoRR
Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2022 J jnl
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence.
J. Mach. Learn. Res.
Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
2022 A* conf
Optimal Rates for Regularized Conditional Mean Embedding Learning.
NeurIPS
Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2022 J jnl
Optimal Rates for Regularized Conditional Mean Embedding Learning.
CoRR
Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2020 A conf
Kernel Conditional Density Operators.
AISTATS
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2020 J jnl
Kernel autocovariance operators of stationary processes: Estimation and convergence.
CoRR
Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
2020 J jnl
Nonparametric approximation of conditional expectation operators.
CoRR
Mattes Mollenhauer, Péter Koltai
2019 J jnl
Kernel Conditional Density Operators.
CoRR
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2018 J jnl
On Hyperparameter Search in Cluster Ensembles.
CoRR
Luzie Helfmann, Johannes von Lindheim, Mattes Mollenhauer, Ralf Banisch