2 papers
cs.LG2026
Space-sampled Value Decay: Forgetting Mechanisms for Non-stationary Reinforcement Learning
Felix Störck, Fabian Hinder, Philipp Hartmann +2
Reinforcement Learning agents deployed on physical systems must adapt continually, since degradation and shifting environment conditions change the dynamics (they \emph{drift}) ove…
cs.LG2025
Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
Felix Störck, Fabian Hinder, Barbara Hammer
With the on-going integration of machine learning systems into the everyday social life of millions the notion of fairness becomes an ever increasing priority in their development.…