Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Miura, Keiji"'
We study the geometry of tropical Fermat-Weber points in terms of the symmetric tropical metric over the tropical projective torus. It is well known that a tropical Fermat-Weber point of a given sample is not unique and in this paper we show that the
Externí odkaz:
http://arxiv.org/abs/2402.14287
We introduce a simple, easy to implement, and computationally efficient tropical convolutional neural network architecture that is robust against adversarial attacks. We exploit the tropical nature of piece-wise linear neural networks by embedding th
Externí odkaz:
http://arxiv.org/abs/2402.00576
Deep neural networks show great success when input vectors are in an Euclidean space. However, those classical neural networks show a poor performance when inputs are phylogenetic trees, which can be written as vectors in the tropical projective toru
Externí odkaz:
http://arxiv.org/abs/2309.13410
In the last decade, developments in tropical geometry have provided a number of uses directly applicable to problems in statistical learning. The TML package is the first R package which contains a comprehensive set of tools and methods used for basi
Externí odkaz:
http://arxiv.org/abs/2309.01082
We consider a minimum enclosing and maximum inscribed tropical balls for any given tropical polytope over the tropical projective torus in terms of the tropical metric with the max-plus algebra. We show that we can obtain such tropical balls via line
Externí odkaz:
http://arxiv.org/abs/2303.02539
Publikováno v:
Alg. Stat. 14 (2023) 37-69
In this paper we propose Hit and Run (HAR) sampling from a tropically convex set. The key ingredient of HAR sampling from a tropically convex set is sampling uniformly from a tropical line segment over the tropical projective torus, which runs linear
Externí odkaz:
http://arxiv.org/abs/2209.15045
Much evidence from biological theory and empirical data indicates that, gene tree, phylogenetic trees reconstructed from different genes (loci), do not have to have exactly the same tree topologies. Such incongruence between gene trees might be cause
Externí odkaz:
http://arxiv.org/abs/2206.04206
Autor:
Miura, Keiji, Yoshida, Ruriko
In this research, we investigate a tropical principal component analysis (PCA) as a best-fit Stiefel tropical linear space to a given sample over the tropical projective torus for its dimensionality reduction and visualization. Especially, we charact
Externí odkaz:
http://arxiv.org/abs/2112.11893
Support Vector Machines (SVMs) are one of the most popular supervised learning models to classify using a hyperplane in an Euclidean space. Similar to SVMs, tropical SVMs classify data points using a tropical hyperplane under the tropical metric with
Externí odkaz:
http://arxiv.org/abs/2101.11531
Publikováno v:
In Neural Networks January 2023 157:77-89