Author

Gian Antonio Susto

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#machine learning Preprint Oct 2026

Finite-Time Guarantees for Constrained Reinforcement Learning under Partial Observability

We study reinforcement learning in constrained partially observable Markov decision processes (CPOMDPs), where an agent maximizes reward subject to a cost constraint using only incomplete information about the underlying state. The lack of state observability may require optimal policies to depend on arbitrarily long o...

Valentina Zaccaria, P. Jordan, Ting-Ting Ni et al. · 0 citations

#machine learning Preprint Aug 2026

Uncertainty and Business-Aware Remaining Useful Life Estimation for Semiconductor Manufacturing

Semiconductor manufacturing relies on tightly interconnected components, so early identification of the assets most likely to fail is essential to prevent a single breakdown from disrupting the entire production pipeline. Maintenance planning must therefore balance unexpected failures against prematurely interrupted op...

Davide Frizzo, Francesco Borsatti, Gian Antonio Susto · 0 citations

#artificial intelligence Jul 2026

TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series

TypiCore is proposed, a novel hybrid query strategy that alternates between typicality-based and diversity-based sample selection across active learning cycles, enabling the construction of memory buffers that are both representative and diverse.

G. Szücs, Samuel Jacsev, Marcell Németh et al. · arXiv.org · 0 citations