In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been ...
Much of the text of pen resources such as Wikipedia is written at a college level of readability, thus posing an access barrier to the general public. Reading levels are important ...
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...