We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
: This paper presents a novel adaptive course composition system that based on mashing up learning content in a web application. The system includes three major components, static ...
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Unsupervised over-segmentation of an image into superpixels
is a common preprocessing step for image parsing
algorithms. Superpixels are used as both regions of support
for feat...
Alastair P. Moore, Simon J. D. Prince, Jonathan Wa...