Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
—To survive and succeed, software projects need to attract and retain contributors. We model the individual’s chances to become a valuable contributor through her capacity, wil...
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
Currently, large-scale projects are underway to perform whole genome disease association studies. Such studies involve the genotyping of hundreds of thousands of SNP markers. One o...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...