Motivation Most modern machine learning algorithms are all based on the same feature weighing framework, i.e. . In order to capture the possible inter-relationship between features, the prevalent way is to expand the feature set by including interactive terms. However, this process is very ad-hoc, and it depends on a lot of manual trial-errors. Proposal
Category: Ongoing Researches
Two-dimensional Proximal Constraints with Group Lasso for Disease Progression Prediction
Abstract Despite the advance in medical research, there are still some diseases that cannot be cured after certain level of severity. For instance, Alzheimer’s disease (AD), arguably the best known neurodegenerative disease, attracts significant attention because of its irreversible disease progression. Enormous capital and efforts have been invested into AD research for the pursuit of
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