We address the problem of building a clustering as a subset of a (possibly large) set of candidate clusters under user-defined constraints. In contrast to most approaches to constrained clustering, we do not constrain the way observations can be grouped into clusters, but the way candidate clusters can be combined into suitable clusterings. The constraints may concern the type of clustering (e....

An exact algorithm is developed for the chance-constrained multi-area reserve sizing problem in presence of transmission network constraints. The can be cast as a two-stage stochastic mixed integer linear program using sample approximation. Due to complicated structure problem, existing methods attempt find feasible solution based on heuristics. Existing mixed-integer algorithms that applied di...

In this paper, we study possible extensions of the main ideas and methods constrained DC optimization to case nonlinear semidefinite programming problems more general nonsmooth cone problems. first part analyse two different approaches definition matrix-valued functions (namely, order-theoretic componentwise), some properties convex mappings demonstrate how compute decompositions constraints ap...

Soft Robotics In article number 2300535, Robert Baines, Rebecca Kramer-Bottiglio, and co-workers report an inverse design method to realize inflatables that match diverse 3D target curves. The estimates the geometry location of stiffer material patches that, when applied inflatable's surface, program curvature torsion along its length. Examples new complex robotic manipulation functionality ena...

Most existing architectural studies on ReRAM-based processing-in-memory (PIM) DNN accelerators assume that all weights of the can be mapped to crossbar at once. However, these are over-idealized. ReRAM resources for calculation limited because technological limitations, so multiple weight mapping procedures required during inference process. In this paper, we propose a static scheduling framewo...