Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
Statistical static timing analysis (SSTA) has been a popular research topic in recent years. A fundamental issue with applying SSTA in practice today is the lack of reliable and e...
Histograms have been widely used for fast estimation of query result sizes in query optimization. In this paper, we propose a new histogram method, called the Skew-Tolerant Histog...
Yohan J. Roh, Jae Ho Kim, Yon Dohn Chung, Jin Hyun...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Large-scale comparison of genomic DNA is of fundamental importance in annotating functional elements of genomes. To perform large comparisons efficiently, BLAST (Methods: Companio...