Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
We present a new approach to integrated motion estimation and segmentation by combining methods from discrete and continuous optimization. The velocity of each of a set of regions ...
Abstract. We extend the setting of Satisfiability Modulo Theories (SMT) by introducing a theory of costs C, where it is possible to model and reason about resource consumption and ...
This paper considers the issue of bulk loading large data sets for the UB-Tree, a multidimensional index structure. Especially in dataware housing (DW), data mining and OLAP it is...
Robert Fenk, Akihiko Kawakami, Volker Markl, Rudol...
A novel self-trimming algorithm for A/D converters [1,2] has been presented which continually trims thresholds in the flash A/D subconverters of two-stage and pipelined A/D conver...