Abstract: In this article, we present an efficient unified algorithm for the minimum Euclidean distance between two collections of compact convex sets, each of which can be a collection of convex ...

1 School of Electronic and Information Engineering, Beijing Jiaotong University, China 2 School of Automation and Intelligence, Beijing Jiaotong University, China Recently, deep unfolding networks ...

Department of Chemistry, Lancaster University, Lancaster LA1 4YW, U.K. School of Chemistry, University of East Anglia, Norwich NR4 7TJ, U.K.

1 Microelectronics and Semiconductors Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia 2 Advanced Materials Institute, King Abdulaziz City for Science and ...

ABSTRACT: Purpose: This study describes a machine-learning approach utilizing patients' anatomical changes to predict parotid mean dose changes in fractionated radiotherapy for head-and-neck cancer, ...

Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, ...

Explaining how structure of the brain gives rise to its emerging dynamics is a primary pursuit in neuroscience. We describe a fundamental anatomical constraint that emphasizes the key role of rare ...

This Paper addresses the limitations of classical machine learning approaches primarily developed for data lying in Euclidean space. Modern machine learning increasingly encounters richly structured ...