Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Introducing large-scale problems early in the CS1 course has been shown to be an effective way to teach algorithmic concepts. Adopting this approach in a CS1 course taught in Java,...
Sridhar Narayan, Jack Tompkins, Gene A. Tagliarini
A major focus within the Integrated Chip (IC) industry is reducing power consumption of devices. In this paper, we explore the idea of persistent CAD algorithms that constantly imp...
The pixel purity index algorithm is employed in remote sensing for analyzing hyperspectral images. A single pixel usually covers several different materials, and its observed spect...
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
Minimum Error Rate Training is the algorithm for log-linear model parameter training most used in state-of-the-art Statistical Machine Translation systems. In its original formula...
Abstract. Current mobile digital communication systems must implement rigorous operations to guarantee high levels of confidentiality and integrity during transmission of critical ...
Abstract. In this paper we tackle the problem of coordinating multiple decentralised agents with continuous state variables. Specifically we propose a hybrid approach, which combin...
Thomas Voice, Ruben Stranders, Alex Rogers, Nichol...
The least common subsumer (lcs) w.r.t general EL-TBoxes does not need to exists in general due to cyclic axioms. In this paper we present an algorithm for computing role-depth boun...
Abstract. Data compression has been widely applied in many data processing areas. Compression methods use variable-length codes with the shorter codes assigned to symbols or groups...