The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, S...
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon
This work describes how evolutionary computation can be used to synthesize lowlevel image operators that detect interesting points on digital images. Interest point detection is a...
Dirty data is a serious problem for businesses leading to incorrect decision making, inefficient daily operations, and ultimately wasting both time and money. Dirty data often ari...