In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
ABSTRACT Motivated by data value locality and quality tolerance present in multimedia applications, we propose a new micro-architecture, Region-level Approximate Computation Buffer...
—Increasing energy consumption in server consolidation environments leads to high maintenance costs for data centers. Main memory, no less than processor, is a major energy consu...
Jae-Wan Jang, Myeongjae Jeon, Hyo-Sil Kim, Heeseun...
This paper is concerned with the reconstruction of perfect phylogenies from binary character data with missing values, and related problems of inferring complete haplotypes from h...
Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching f...