We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
We present an online algorithm for planning sequences of footstep locations that encode goal-directed navigation strategies for humanoid robots. Planning footsteps is more general...
James J. Kuffner Jr., Satoshi Kagami, Koichi Nishi...
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
Simulation composability is a difficult capability to achieve due to the challenges of creating components, selecting combinations of components, and integrating the selected comp...
Michael Roy Fox, David C. Brogan, Paul F. Reynolds...
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...