2 citations · 7 across the 7 of their papers we have counts for
7 papers
The Continuous Stochastic Gradient Method: Part II -- Application and Numerics
Max Grieshammer, Lukas Pflug, Michael Stingl +1
In this contribution, we present a numerical analysis of the continuous stochastic gradient (CSG) method, including applications from topology optimization and convergence rates. I…
The Continuous Stochastic Gradient Method: Part I -- Convergence Theory
Max Grieshammer, Lukas Pflug, Michael Stingl +1
In this contribution, we present a full overview of the continuous stochastic gradient (CSG) method, including convergence results, step size rules and algorithmic insights. We con…
CSG: A stochastic gradient method for a wide class of optimization problems appearing in a machine learning or data-driven context
Lukas Pflug, Max Grieshammer, Andrian Uihlein +1
A recent article introduced thecontinuous stochastic gradient method (CSG) for the efficient solution of a class of stochastic optimization problems. While the applicability of kno…
Measure representation of evolving genealogies
Max Grieshammer
We study evolving genealogies, i.e. processes that take values in the space of (marked) ultra-metric measure spaces and satisfy some sort of "consistency" condition. This condition…
Family size decomposition of genealogical trees
Max Grieshammer
We study the path of family size decompositions of varying depth of genealogical trees. We prove that this decomposition as a function on (equivalence classes of) ultra-metric meas…
Genealogical distance under selection
Max Grieshammer
We study the genealogical distance of two randomly chosen individuals in a population that evolves according to a two type Moran model with mutation and selection. We prove that th…