Preferences in constraint problems are common but significant in many real world applications. In this paper, we extend our conditional and composite CSP (CCCSP) framework, managi...
Abstract. The generic (aka. black-box) group model is a valuable methodology for analyzing the computational hardness of number-theoretic problems used in cryptography. Since the p...
Andy Rupp, Gregor Leander, Endre Bangerter, Alexan...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
The conditional covering problem (CCP) aims to locate facilities on a graph, where the vertex set represents both the demand points and the potential facility locations. The proble...