Improvisation is rapidly becoming an important issue for both scholars and practitioners. Organizations that operate in turbulent environments must learn to swiftly adapt and resp...
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
In this paper, a novel algorithm for bandwidth reduction in adaptive distributed learning is introduced. We deal with diffusion networks, in which the nodes cooperate with each ot...
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, ...
When preparing students for an industrial or academic career in software engineering, educational institutions need to address the globally distributed character of the software en...
Kevin Dullemond, Ben van Gameren, Rini van Solinge...