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stat.ML2025
Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
Andrzej Cichocki
In this paper, we develop a wide class Mirror Descent (MD) algorithms, which play a key role in machine learning. For this purpose we formulated the constrained optimization proble…
cs.LG2025
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…
cs.LG2025
Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS
Andrzej Cichocki
This paper investigates in depth the fundamental properties of the two-parameter generalized Euler logarithm and its inverse, the associated deformed -exponential function.…