HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
Feedback-directed optimization (FDO) is effective in improving application runtime performance, but has not been widely adopted due to the tedious dual-compilation model, the dif...
Dehao Chen, Neil Vachharajani, Robert Hundt, Shih-...
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma