Model order reduction is an efficient technique to reduce the system complexity while producing a good approximation of the input-output behavior. However, the efficiency of reduc...
Boyuan Yan, Lingfei Zhou, Sheldon X.-D. Tan, Jie C...
Motivation: Genome maps are fundamental to the study of an organism and essential in the process of genome sequencing which in turn provides the ultimate map of the genome. The in...
Thomas Faraut, Simon de Givry, Patrick Chabrier, T...
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
We study the problem of formally verifying shared memory multiprocessor executions against memory consistency models--an important step during post-silicon verification of multipro...