Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Increasingly scientists are using collections of software tools in their research. These tools are typically used in concert, often necessitating laborious and error prone manual ...
We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classific...
Timothy Meekhof, Gary W. Daughdrill, Robert B. Hec...
This paper presents a method for optimizing prostate needle biopsy, by creating a statistical atlas of the spatial distribution of prostate cancer from a large patient cohort. In ...
Dinggang Shen, Zhiqiang Lao, Edward Herskovits, Ga...
Interest in synthesis of Application Specific Instruction Set Processors or ASIPs has increased considerably and a number of methodologies have been proposed for ASIP design. A ke...
Manoj Kumar Jain, Lars Wehmeyer, Stefan Steinke, P...