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cs.LG2025
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design
Yasir Zubayr Barlas, Kizito Salako
Recent developments in sequential experimental design look to construct a policy that can efficiently navigate the design space, in a way that maximises the expected information ga…
cs.LG2024
Derivative-based regularization for regression
Enrico Lopedoto, Maksim Shekhunov, Vitaly Aksenov +2
In this work, we introduce a novel approach to regularization in multivariable regression problems. Our regularizer, called DLoss, penalises differences between the model's derivat…