Equivalence between the Fitness-Complexity and the Sinkhorn-Knopp algorithms

Autor: D Mazzilli, M S Mariani, F Morone, A Patelli

Publikováno v: Journal of Physics: Complexity, Vol 5, Iss 1, p 015010 (2024)

We uncover the connection between the Fitness-Complexity algorithm, developed in the economic complexity field, and the Sinkhorn–Knopp algorithm, widely used in diverse domains ranging from computer science and mathematics to economics. Despite min

Externí odkaz: https://doaj.org/article/bbc8979dffb44de8949b30bbb686f004

Regularized Optimal Transport Based on an Adaptive Adjustment Method for Selecting the Scaling Parameters of Unscented Kalman Filters

Autor: Chang Ho Kang, Sun Young Kim

Publikováno v: Sensors, Vol 22, Iss 3, p 1257 (2022)

In this paper, an adaptation method for adjusting the scaling parameters of an unscented Kalman filter (UKF) is proposed to improve the estimation performance of the filter in dynamic conditions. The proposed adaptation method is based on a sequentia

Externí odkaz: https://doaj.org/article/3ead203ee79c4218842bc096180fb0d2

Overrelaxed Sinkhorn–Knopp Algorithm for Regularized Optimal Transport

Autor: Alexis Thibault, Lénaïc Chizat, Charles Dossal, Nicolas Papadakis

Publikováno v: Algorithms, Vol 14, Iss 5, p 143 (2021)

This article describes a set of methods for quickly computing the solution to the regularized optimal transport problem. It generalizes and improves upon the widely used iterative Bregman projections algorithm (or Sinkhorn–Knopp algorithm). We firs

Externí odkaz: https://doaj.org/article/5cd82482c2b24463bdc0e2b4442950fc

Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification

Autor: Joakim Bruslund Haurum, Meysam Madadi, Sergio Escalera, Thomas B. Moeslund

Publikováno v: Haurum, J B, Madadi, M, Guerrero, S E & Moeslund, T B 2022, ' Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification ', Automation in Construction, vol. 144, 104614 . https://doi.org/10.1016/j.autcon.2022.104614

A crucial part of image classification consists of capturing non-local spatial semantics of image content. This paper describes the multi-scale hybrid vision transformer (MSHViT), an extension of the classical convolutional neural network (CNN) backb

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::698a8c11f40098b4308d0cd4b2a98dde
https://vbn.aau.dk/ws/files/492073391/1_s2.0_S0926580522004848_main.pdf

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