Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Abstract. We present a reduction semantics for the LYSA calculus extended with session information, for modelling cryptographic protocols, and a static analysis for it. If a protoc...
Han Gao, Chiara Bodei, Pierpaolo Degano, Hanne Rii...
—We consider the problem of positioning a cloud of points in the Euclidean space Rd , from noisy measurements of a subset of pairwise distances. This task has applications in var...