We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
— This article compares several parameterizations and motion models for improving the estimation of the nonlinear uncertainty distribution produced by robot motion. In previous w...
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
We survey logic-based and automata-based languages and techniques for the speci cation and veri cation of real-time systems. In particular, we discuss three syntactic extensions of...
—Traditional hierarchical namespaces are not sufficient for representing and managing the rich semantics of today’s storage systems. In this paper, we discuss the principles o...
Zhichen Xu, Magnus Karlsson, Chunqiang Tang, Chris...