Author

L. Nanni

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Open access Sep 2026

Integrating Deep Neural Networks with Support Vector Machines for Gene Expression Classification

Gene expression classification remains a challenging task due to the high dimensionality and heterogeneity of available datasets. In this study, we present a comprehensive empirical analysis combining neural networks and Support Vector Machines (SVMs) for gene expression classification. We evaluate a wide range of arch...

L. Nanni, C. Salvatore, Niccolò Frassetto et al. · Electronics · 0 citations

Preprint Aug 2026

A Progressive Design Study of Visual Encoders and Value Estimation for Replay-Free Parallelized Q-Learning

Results show that visual topology, multiplicative representation, and downstream value-estimation design can substantially affect replay-free Q-learning, and that their benefits should be evaluated jointly with computational complexity.

Taha Shieenavaz, Shabnam Zareshahraki, L. Nanni · 0 citations

#machine learning Preprint Aug 2026

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks

Recent advancements in deep reinforcement learning have increasingly favored simplified, highly parallelized paradigms. Notably, the Parallelized Q-Network (PQN) algorithm enables off-policy value learning without relying on experience replay buffers or target networks. However, the representational capacity and comput...

Taha Shieenavaz, Shabnam Zareshahraki, L. Nanni · 0 citations