65 citations · 65 across the 4 of their papers we have counts for
4 papers
The alpha-beta divergence for real and complex data
Sergio Cruces
Divergences are fundamental to the information criteria that underpin most signal processing algorithms. The alpha-beta family of divergences, designed for non-negative data, offer…
Mirror Descent and Novel Exponentiated Gradient Algorithms Using Trace-Form Entropies and Deformed Logarithms
Andrzej Cichocki, Toshihisa Tanaka, Frank Nielsen +1
This paper introduces a broad class of Mirror Descent (MD) and Generalized Exponentiated Gradient (GEG) algorithms derived from trace-form entropies defined via deformed logarithms…
Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection
Andrzej Cichocki, Sergio Cruces, Auxiliadora Sarmiento +1
This paper introduces a novel family of generalized exponentiated gradient (EG) updates derived from an Alpha-Beta divergence regularization function. Collectively referred to as E…
Log-Determinant Divergences Revisited: Alpha--Beta and Gamma Log-Det Divergences
Andrzej Cichocki, Sergio Cruces, Shun-Ichi Amari
In this paper, we review and extend a family of log-det divergences for symmetric positive definite (SPD) matrices and discuss their fundamental properties. We show how to generate…