To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
A new algorithm for context modeling of binary sources with application to video compression is presented. Our proposed method is based on a tree rearrangement and tree selection ...
We describe the implementation and experimental evaluation of a fault-tolerant leader election service for dynamic systems. Intuitively, distributed applications can use this serv...
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...