Abstract. We consider an upper confidence bound algorithm for Markov decision processes (MDPs) with deterministic transitions. For this algorithm we derive upper bounds on the onl...
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Internet routing is mostly based on static information-it's dynamicity is limited to reacting to changes in topology. Adaptive performance-based routing decisions would not o...
Ioannis C. Avramopoulos, Jennifer Rexford, Robert ...