Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
We propose a novel approach, called Dynamic Fractional Resource Scheduling (DFRS), to share homogeneous cluster computing platforms among competing jobs. DFRS leverages virtual mac...
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while in...