Mar 23, 2016 · The MM subspace algorithm which has been introduced more recently has shown good practical performance when compared with other methods on ...
Oct 24, 2016 · This paper aims at deriving such convergence rates both for batch and online versions of the algorithm and, in particular, discusses the ...
Jul 19, 2016 · This paper aims at deriving such convergence rates both for batch and online versions of the algorithm and, in particular, discusses the.
The convergence rate is im- proved by using information from past iterates for the construction of new estimates. Another efficient way to accelerate the ...
(PDF) Convergence Rate Analysis of the Majorize-Minimize ...
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The MM subspace algorithm which has been introduced more recently has shown good practical performance when compared with other methods on various optimization ...
Aug 10, 2016 · This paper aims at deriving such conver- gence rates both for batch and online versions of the algorithm, and in particular, discusses the ...
Jan 25, 2023 · The convergence rate is im- proved by using information from past iterates for the construction of new estimates. Another efficient way to ...
Dec 6, 2021 · This paper provides new insights about the convergence guarantees of block alternating MM schemes, in the challenging non-convex setting, and ...
The MM subspace algorithm that has been introduced more recently has shown good practical performance when compared with other methods on various optimization ...
We propose an accelerated gradient descent approach which combines three strategies, namely (i) a variable metric derived from the majorization-minimization ...
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