Massimiliano Pontil

This paper introduces a morphology-agnostic regularization framework for image deconvolution in single-photon-sensitive microscopy, eliminating semi-convergence and improving reconstruction quality.

The paper proposes a framework combining neuroimaging and clinical data for mental health diagnosis using EasyMKL and feature selection, showing improved performance over baseline methods.