In order to build a data structure that is extensible and reusable, it is necessary to decouple the intrinsic and primitive behavior of the structure from the application specific...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
—Approximating ideal program outputs is a common technique for solving computationally difficult problems, for adhering to processing or timing constraints, and for performance ...
Jason Ansel, Yee Lok Wong, Cy P. Chan, Marek Olsze...
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...