Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require effici...
The goal of this paper is to develop an algebraic theory of process scheduling. We specify a syntax for denoting processes composed of actions with given durations. Subsequently, w...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...