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pro vyhledávání: '"Kirches, Christian"'
The combinatorial integral approximation (CIA) is a solution technique for integer optimal control problems. In order to regularize the solutions produced by CIA, one can minimize switching costs in one of its algorithmic steps. This leads to combina
Externí odkaz:
http://arxiv.org/abs/2305.12846
Gradient-based methods have been highly successful for solving a variety of both unconstrained and constrained nonlinear optimization problems. In real-world applications, such as optimal control or machine learning, the necessary function and deriva
Externí odkaz:
http://arxiv.org/abs/2302.07205
Publikováno v:
Journal of Nonsmooth Analysis and Optimization, Volume 4, Original research articles (July 25, 2023) jnsao:10164
Binary trust-region steepest descent (BTR) and combinatorial integral approximation (CIA) are two recently investigated approaches for the solution of optimization problems with distributed binary-/discrete-valued variables (control functions). We sh
Externí odkaz:
http://arxiv.org/abs/2202.07934
Statistical matching methods are widely used in the social and health sciences to estimate causal effects using observational data. Often the objective is to find comparable groups with similar covariate distributions in a dataset, with the aim to re
Externí odkaz:
http://arxiv.org/abs/2101.07029
We propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to obtain an es
Externí odkaz:
http://arxiv.org/abs/2009.14047
Publikováno v:
Journal of Nonsmooth Analysis and Optimization, Volume 2, Original research articles (February 18, 2021) jnsao:6673
This work continues an ongoing effort to compare non-smooth optimization problems in abs-normal form to Mathematical Programs with Complementarity Constraints (MPCCs). We study general Nonlinear Programs with equality and inequality constraints in ab
Externí odkaz:
http://arxiv.org/abs/2007.14653
Publikováno v:
Journal of Nonsmooth Analysis and Optimization, Volume 2, Original research articles (February 18, 2021) jnsao:6672
This work is part of an ongoing effort of comparing non-smooth optimization problems in abs-normal form to MPCCs. We study the general abs-normal NLP with equality and inequality constraints in relation to an equivalent MPCC reformulation. We show th
Externí odkaz:
http://arxiv.org/abs/2007.14654
Autor:
Friese, Jana, Brandt, Niklas, Schulte, Andreas, Kirches, Christian, Tegethoff, Wilhelm, Köhler, Jürgen
Publikováno v:
In Energy and AI April 2023 12
Propensity score matching (PSM) is the de-facto standard for estimating causal effects in observational studies. We show that PSM and its implementations are susceptible to several major drawbacks and illustrate these findings using a case study with
Externí odkaz:
http://arxiv.org/abs/1803.02704
Publikováno v:
In Computers and Chemical Engineering October 2021 153