We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
— The purpose of this case study is to create a competitive operative management system for efficiency and quality performance for a company running maintenance service business ...
Mesh generation is a critical step in high fidelity computational simulations. High-quality and high-density meshes are required to accurately capture the complex physical phenome...
Yasushi Ito, Alan M. Shih, Anil K. Erukala, Bharat...
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...