5 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
Data-driven optimal stopping: A pure exploration analysis
Sören Christensen, Niklas Dexheimer, Claudia Strauch
The standard theory of optimal stopping is based on the idealised assumption that the underlying process is essentially known. In this paper, we drop this restriction and study dat…
Data-driven rules for multidimensional reflection problems
Sören Christensen, Asbjørn Holk Thomsen, Lukas Trottner
Over the recent past data-driven algorithms for solving stochastic optimal control problems in face of model uncertainty have become an increasingly active area of research. Howeve…
Is Learning in Biological Neural Networks based on Stochastic Gradient Descent? An analysis using stochastic processes
Sören Christensen, Jan Kallsen
In recent years, there has been an intense debate about how learning in biological neural networks (BNNs) differs from learning in artificial neural networks. It is often argued th…