no code implementations • 1 Feb 2024 • Kurt Pasque, Christopher Teska, Ruriko Yoshida, Keiji Miura, Jefferson Huang
We introduce a simple, easy to implement, and computationally efficient tropical convolutional neural network architecture that is robust against adversarial attacks.
1 code implementation • 3 Sep 2023 • David Barnhill, Ruriko Yoshida, Georgios Aliatimis, Keiji Miura
In the last decade, developments in tropical geometry have provided a number of uses directly applicable to problems in statistical learning.
no code implementations • 30 Jun 2023 • Ruriko Yoshida
When we apply comparative phylogenetic analyses to genome data, it is a well-known problem and challenge that some of given species (or taxa) often have missing genes.
no code implementations • 9 Jun 2022 • Ruriko Yoshida, David Barnhill, Keiji Miura, Daniel Howe
In order to discover ``outlying'' gene trees which do not follow the ``main distribution(s)'' of trees, we propose to apply the ``tropical metric'' with the max-plus algebra from tropical geometry to a non-parametric estimation of gene trees over the space of phylogenetic trees.
1 code implementation • 30 Nov 2021 • Yixuan Liu, Chrysafis Vogiatzis, Ruriko Yoshida, Erich Morman
Uncrewed autonomous vehicles (UAVs) have made significant contributions to reconnaissance and surveillance missions in past US military campaigns.
no code implementations • 26 Nov 2021 • Patrick Urrutia, David Wren, Chrysafis Vogiatzis, Ruriko Yoshida
County officials can provide targeted information, preparedness training, as well as increase testing in these areas.
no code implementations • 27 Jan 2021 • Ruriko Yoshida, Misaki Takamori, Hideyuki Matsumoto, Keiji Miura
Similar to SVMs, tropical SVMs classify data points using a tropical hyperplane under the tropical metric with the max-plus algebra.
no code implementations • 13 May 2020 • Ruriko Yoshida
Phylogenomics is a new field which applies to tools in phylogenetics to genome data.
2 code implementations • 2 Mar 2020 • Xiaoxian Tang, Houjie Wang, Ruriko Yoshida
For hard margin tropical SVMs, we prove the necessary and sufficient conditions for two categories of data points to be separated, and we show an explicit formula for the optimal value of the feasible linear programming problem.
1 code implementation • 7 Oct 2017 • Ruriko Yoshida, Leon Zhang, Xu Zhang
Principal component analysis is a widely-used method for the dimensionality reduction of a given data set in a high-dimensional Euclidean space.
Combinatorics Populations and Evolution