We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
In this paper we proposed quasi-Newton and limited memory quasi-Newton methods for objective functions defined on Grassmannians or a product of Grassmannians. Specifically we defin...
Extracting entities (such as people, movies) from documents and identifying the categories (such as painter, writer) they belong to enable structured querying and data analysis ov...
— Image-based navigation paradigms have recently emerged as an interesting alternative to conventional modelbased methods in mobile robotics. In this paper, we augment the existi...
In this paper we explore database segmentation in the context of a column-store DBMS targeted at a scientific database. We present a novel hardware- and scheme-oblivious segmentati...