Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
We present efficient support for generalized arrays of parallel data driven objects. Array elements are regular C++ objects, and are scattered across the parallel machine. An indi...
Image processing applications tend to access their data non-sequentially and reuse that data infrequently. As a result, they tend to perform poorly on conventional memory systems ...
Lixin Zhang, John B. Carter, Wilson C. Hsieh, Sall...
Electronic patient records (EPRs) are a valuable resource for research but for confidentiality reasons they cannot be used freely. In order to make EPRs available to a wider group...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...