3 papers
cs.LG2025
Frugality in second-order optimization: floating-point approximations for Newton's method
Giuseppe Carrino, Elena Loli Piccolomini, Elisa Riccietti +1
Minimizing loss functions is central to machine-learning training. Although first-order methods dominate practical applications, higher-order techniques such as Newton's method can…
cs.CV2025
Blind Restoration of High-Resolution Ultrasound Video
Chu Chen, Kangning Cui, Pasquale Cascarano +3
Ultrasound imaging is widely applied in clinical practice, yet ultrasound videos often suffer from low signal-to-noise ratios (SNR) and limited resolutions, posing challenges for d…
math.NA2024
A data-dependent regularization method based on the graph Laplacian
Davide Bianchi, Davide Evangelista, Stefano Aleotti +3
We investigate a variational method for ill-posed problems, named , which embeds a graph Laplacian operator in the regularization term. The novelty of this met…