2 papers
cs.LG2026
Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression
Lorenzo Nikiforos, Luciano Prono, Charalampos Antoniadis +3
The increasing scale of Deep Neural Networks (DNNs) introduces the need for compression techniques such as pruning, quantization, and low-rank decomposition. While these methods ar…
eess.SY2025
Robust Load Disturbance Rejection in PWM DC-DC Buck Converters
Simone Pirrera, Francesco Gabriele, Davide Lena +3
This paper presents a novel approach to robust load disturbance rejection in DC-DC Buck converters. We propose a novel control scheme based on the design of two nested feedback loo…