Matrix optimization with orthogonal constraints appear in a variety of application fields including signal and image processing. Several researchers have developed algorithms for...
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
—In this contribution we provide a thorough stability analysis of gradient type algorithms with non-symmetric matrix step-sizes. We hereby extend existing analyses for symmetric ...
Abstract. A new iterative algorithm for the solution of minimization problems in infinitedimensional Hilbert spaces which involve sparsity constraints in form of p-penalties is pro...
Consider a distributed network of n nodes that is connected to a global source of “beats”. All nodes receive the “beats” simultaneously, and operate in lock-step. A scheme ...