Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
Reuse distance (i.e. LRU stack distance) precisely characterizes program locality and has been a basic tool for memory system research since the 1970s. However, the high cost of m...
Xipeng Shen, Jonathan Shaw, Brian Meeker, Chen Din...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Abstract--Transactional Memory (TM) is an emerging technology which promises to make parallel programming easier. However, to be efficient, underlying TM system should protect only...
This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data. The strategy is to formulate 3D reconstruction as a stati...