Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
This paper explores a topological perspective of planning in the presence of uncertainty, focusing on tasks specified by goal states in discrete spaces. The paper introduces stra...
Subspace identification has proven useful when identifying identifying multi-input multi-output systems. It is, however, important in many applications to take a priori structural ...
Abstract--In double patterning lithography (DPL) layout decomposition for 45nm and below process nodes, two features must be assigned opposite colors (corresponding to different ex...
Andrew B. Kahng, Chul-Hong Park, Xu Xu, Hailong Ya...
—Constrained Genetic Programming (CGP) is a method of searching the Genetic Programming search space non-uniformly, giving preferences to certain subspaces according to some heur...