Zobrazeno 1 - 10
of 90 390
pro vyhledávání: '"Mathematics - Optimization and Control"'
Autor:
Laguzet, Laetitia, Turinici, Gabriel
Publikováno v:
Bull Math Biol 77, 1955-1984 (2015)
The vaccination against ongoing epidemics is seldom compulsory but remains one of the most classical means to fight epidemic propagation. However recent debates concerning the innocuity of vaccines and their risk with respect to the risk of the epide
Externí odkaz:
http://arxiv.org/abs/2410.03567
We study differentiable strongly quasiconvex functions for providing new properties for algorithmic and monotonicity purposes. Furthemore, we provide insights into the decreasing behaviour of strongly quasiconvex functions, applying this for establis
Externí odkaz:
http://arxiv.org/abs/2410.03534
Autor:
Wiesel, Johannes, Xu, Xingyu
We study the quadratically regularized optimal transport (QOT) problem for quadratic cost and compactly supported marginals $\mu$ and $\nu$. It has been empirically observed that the optimal coupling $\pi_\epsilon$ for the QOT problem has sparse supp
Externí odkaz:
http://arxiv.org/abs/2410.03425
Autor:
González-Sanz, Alberto, Nutz, Marcel
The quadratically regularized optimal transport problem is empirically known to have sparse solutions: its optimal coupling $\pi_{\varepsilon}$ has sparse support for small regularization parameter $\varepsilon$, in contrast to entropic regularizatio
Externí odkaz:
http://arxiv.org/abs/2410.03353
Robust optimization aims to find optimum points from the collection of points that are feasible for every possible scenario of a given uncertain set. An optimum solution to a robust optimization problem is commonly found by the min-max robust counter
Externí odkaz:
http://arxiv.org/abs/2410.03222
Autor:
Kim, Jihun, Lavaei, Javad
This paper studies the linear system identification problem in the general case where the disturbance is sub-Gaussian, correlated, and possibly adversarial. First, we consider the case with noncentral (nonzero-mean) disturbances for which the ordinar
Externí odkaz:
http://arxiv.org/abs/2410.03218
Cutting planes (cuts) are crucial for solving Mixed Integer Linear Programming (MILP) problems. Advanced MILP solvers typically rely on manually designed heuristic algorithms for cut selection, which require much expert experience and cannot be gener
Externí odkaz:
http://arxiv.org/abs/2410.03112
We present a policy iteration algorithm for the infinite-horizon N-player general-sum deterministic linear quadratic dynamic games and compare it to policy gradient methods. We demonstrate that the proposed policy iteration algorithm is distinct from
Externí odkaz:
http://arxiv.org/abs/2410.03106
This paper proposes a novel approach to solving nonlinear programming problems using a sharp augmented Lagrangian method with a smoothing technique. Traditional sharp augmented Lagrangian methods are known for their effectiveness but are often hinder
Externí odkaz:
http://arxiv.org/abs/2410.03050
Autor:
Latypov, Ilgam, Dorn, Yuriy
In practical engineering and optimization, solving multi-objective optimization (MOO) problems typically involves scalarization methods that convert a multi-objective problem into a single-objective one. While effective, these methods often incur sig
Externí odkaz:
http://arxiv.org/abs/2410.03023