Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vish...
In numerous application areas fast growing data sets develop with ever higher complexity and dynamics. A central challenge is to filter the substantial information and to communic...
Daniel A. Keim, Florian Mansmann, Daniela Oelke, H...
This paper presents research on developing a new type of software tool for training and assisting the personnel in emergency response planning. The tool, called Disciple-VPT, will...
Gheorghe Tecuci, Mihai Boicu, Thomas Hajduk, Dorin...