We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
In this paper we study the constrained consensus problem, i.e. the problem of reaching a common point from the estimates generated by multiple agents that are constrained to lie in...
The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the foll...
Starting from a certain monoid that describes the geometry of the left self-distributivity identity, we construct an explicit realization of the free left self-distributive system ...