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cs.LG2025
UAMDP: Uncertainty-Aware Markov Decision Process for Risk-Constrained Reinforcement Learning from Probabilistic Forecasts
Michal Koren, Or Peretz, Tai Dinh +1
Sequential decisions in volatile, high-stakes settings require more than maximizing expected return; they require principled uncertainty management. This paper presents the Uncerta…
cs.LG2025★ 5 cited
An upper bound on the silhouette evaluation metric for clustering
Hugo Sträng, Tai Dinh
The silhouette coefficient quantifies, for each observation, the balance between within-cluster cohesion and between-cluster separation, taking values in the range [-1,1]. The aver…