30 citations · 190 across the 36 of their papers we have counts for
3 papers · 1 filter
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds
Alexander Novikov, Maxim Rakhuba, Ivan Oseledets
In scientific computing and machine learning applications, matrices and more general multidimensional arrays (tensors) can often be approximated with the help of low-rank decomposi…
Two-phase approaches to optimal model-based design of experiments: how many experiments and which ones?
Charlie Vanaret, Philipp Seufert, Jan Schwientek +5
Model-based experimental design is attracting increasing attention in chemical process engineering. Typically, an iterative procedure is pursued: an approximate model is devised, p…
Follow the bisector: a simple method for multi-objective optimization
Alexandr Katrutsa, Daniil Merkulov, Nurislam Tursynbek +1
This study presents a novel Equiangular Direction Method (EDM) to solve a multi-objective optimization problem. We consider optimization problems, where multiple differentiable los…