Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
We examine online learning in the context of the Wisconsin Card Sorting Task (WCST), a task for which the concept acquisition strategies for human and other primates are well docu...
Xiaojin Zhu, Michael Coen, Shelley Prudom, Ricki C...
We present a class of models that, via a simple construction,
enables exact, incremental, non-parametric, polynomial-time,
Bayesian inference of conditional measures. The approac...
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Existing online learning experiences lack the social dimension that characterizes learning in the real world. This social dimension extends beyond the traditional classroom into t...
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
A study of how different groups of people find the experience of flexible online learning. A first year course in Internet and Web Design is offered to a diverse range of students...
Many universities and private corporations are investing significant capital in online learning initiatives. Willingness on the part of the student to take part in online learning...
An important requirement for emerging applications which aim to locate and integrate content distributed over the Web is to identify pages that are relevant for a given domain or ...
Our “information-oriented” society shows an increasing exigency of life-long learning. In such framework, online Learning is becoming an important tool to allow the flexibilit...