We relate two problems that have been explored in two distinct communities. The first is the problem of combining expert advice, studied extensively in the computational learning...
We address the problem of constructing randomized online algorithms for the Metrical Task Systems (MTS) problem on a metric against an oblivious adversary. Restricting our attenti...
Jacob Abernethy, Peter L. Bartlett, Niv Buchbinder...
Abstract. We consider the randomized k-server problem, and give improved results for various metric spaces. In particular, we extend a recent result of Cot
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
This paper proposes a novel way of automatically developing data warehouse configuration in rule-based CRM systems. Rule-based CRM systems assume that marketing activities are re...
Han-joon Kim, Taehee Lee, Sang-goo Lee, Jonghun Ch...