Abstract The main purpose of this work is to provide an efficient scheme for constructing kernel-based reduced interpolation models. In the existing literature such problems are mainly addressed via well-established knot insertion or removal schemes. Such iterative strategies usually quite demanding from a computational point view and our goal study implementation data approaches, namely basis ...

Abstract In this paper, a distributed stochastic approximation algorithm is proposed to track the dynamic root of sum time-varying regression functions over network. Each agent updates its estimate by using local observation, information global root, and received from neighbors. Compared with similar works in optimization area, we allow observation be noise-corrupted, noise condition much weake...

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets node and edge types subject length orientation restrictions. show that already deciding feasibility such approximation problems is NP-hard, remains intractable even for very simple setups. then devise an algo...

<p style='text-indent:20px;'>The <inline-formula><tex-math id="M2">\begin{document}$ k $\end{document}</tex-math></inline-formula>-means problem is a classical combinatorial optimization which has lots of applications in many fields such as machine learning, data mining, etc. We consider variant id="M3">\begin{document}$ the spherical space, that is, id="M4">...