Applications of Lagrangian relaxation-based algorithms to industrial scheduling problems, especially in production workshop scenarios: A review
L Sun, R Yang, J Feng, G Guo - Journal of Process Control, 2024 - Elsevier
Industrial scheduling problems (ISPs), especially industrial production workshop scheduling
problems (IPWSPs) in various sectors like manufacturing, and power require allocating …
problems (IPWSPs) in various sectors like manufacturing, and power require allocating …
Leveraging Optimal Transport via Projections on Subspaces for Machine Learning Applications
C Bonet - arxiv preprint arxiv:2311.13883, 2023 - arxiv.org
Optimal Transport has received much attention in Machine Learning as it allows to compare
probability distributions by exploiting the geometry of the underlying space. However, in its …
probability distributions by exploiting the geometry of the underlying space. However, in its …
Accelerated methods for riemannian min-max optimization ensuring bounded geometric penalties
In this work, we study optimization problems of the form $\min_x\max_y f (x, y) $, where $ f (x,
y) $ is defined on a product Riemannian manifold $\mathcal {M}\times\mathcal {N} $ and is …
y) $ is defined on a product Riemannian manifold $\mathcal {M}\times\mathcal {N} $ and is …
A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds
Recently, there has been growing interest in minimax problems on Riemannian manifolds
due to their wide applications in machine learning and signal processing. Although many …
due to their wide applications in machine learning and signal processing. Although many …
On the Oracle Complexity of a Riemannian Inexact Augmented Lagrangian Method for Riemannian Nonsmooth Composite Problems
In this paper, we establish for the first time the oracle complexity of a Riemannian inexact
augmented Lagrangian (RiAL) method with the classical dual update for solving a class of …
augmented Lagrangian (RiAL) method with the classical dual update for solving a class of …
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Optimal transport has been very successful for various machine learning tasks; however, it is
known to suffer from the curse of dimensionality. Hence, dimensionality reduction is …
known to suffer from the curse of dimensionality. Hence, dimensionality reduction is …
[PDF][PDF] Smoothing l1-exact penalty method for intrinsically constrained Riemannian optimization problems
This paper deals with the Constrained Riemannian Optimization (CRO) problem, which
involves minimizing a function subject to equality and inequality constraints on Riemannian …
involves minimizing a function subject to equality and inequality constraints on Riemannian …