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Related papers: Tropical Bisectors and Carlini-Wagner Attacks

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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,…

Combinatorics · Mathematics 2023-01-24 Keiji Miura , Ruriko Yoshida

Graph convolutional networks (GCNs) are vulnerable to perturbations of the graph structure that are either random, or, adversarially designed. The perturbed links modify the graph neighborhoods, which critically affects the performance of…

Machine Learning · Computer Science 2019-10-23 Vassilis N. Ioannidis , Georgios B. Giannakis

We develop a tropical analogue of the classical double description method allowing one to compute an internal representation (in terms of vertices) of a polyhedron defined externally (by inequalities). The heart of the tropical algorithm is…

Computational Geometry · Computer Science 2011-12-30 Xavier Allamigeon , Stephane Gaubert , Eric Goubault

When modeling the dynamics of infectious disease, the incorporation of contact network information allows for the capture of the non-randomness and heterogeneity of realistic contact patterns. Oftentimes, it is assumed that the underlying…

Populations and Evolution · Quantitative Biology 2024-04-17 Maxwell H. Wang , Jukka-Pekka Onnela

Although convolutional neural networks (CNNs) are now widely used in various computer vision applications, its huge resource demanding on parameter storage and computation makes the deployment on mobile and embedded devices difficult.…

Computer Vision and Pattern Recognition · Computer Science 2019-09-26 Zhe Xu , Ray C. C. Cheung

It is challenging to reduce the complexity of neural networks while maintaining their generalization ability and robustness, especially for practical applications. Conventional solutions for this problem incorporate quantum-inspired neural…

Machine Learning · Computer Science 2025-11-13 Andi Chen

In this article, we present a massively parallel framework for computing tropicalizations of algebraic varieties which can make use of finite symmetries. We compute the tropical Grassmannian TGr$_0(3,8)$, and show that it refines the…

Algebraic Geometry · Mathematics 2020-04-02 Dominik Bendle , Janko Boehm , Yue Ren , Benjamin Schröter

This paper investigates one-step backward reachability for uncertain max-plus linear systems with additive disturbances. Given a target set, the problem is to compute the set of states from which there exists an admissible control input…

Systems and Control · Electrical Eng. & Systems 2026-03-31 Yuda Li , Xiang Yin

Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs are subject to attacks such as adversarial perturbation and…

Machine Learning · Computer Science 2019-11-15 Yizhen Dong , Peixin Zhang , Jingyi Wang , Shuang Liu , Jun Sun , Jianye Hao , Xinyu Wang , Li Wang , Jin Song Dong , Dai Ting

We study algebraic and combinatorial aspects of (classical) projections of $m$-dimensional tropical varieties onto $(m+1)$-dimensional planes. Building upon the work of Sturmfels, Tevelev, and Yu on tropical elimination as well as the work…

Algebraic Geometry · Mathematics 2010-04-23 Kerstin Hept , Thorsten Theobald

Geometry and topology of decision regions are closely related with classification performance and robustness against adversarial attacks. In this paper, we use differential geometry to theoretically explore the geometrical and topological…

Machine Learning · Computer Science 2021-04-19 Bo Liu , Mengya Shen

From transportation networks to complex infrastructures, and to social and economic networks, a large variety of systems can be described in terms of multiplex networks formed by a set of nodes interacting through different network layers.…

Social and Information Networks · Computer Science 2015-09-15 Dawei Zhao , Lianhai Wang , Zhen Wang

Recent studies on the adversarial vulnerability of neural networks have shown that models trained to be more robust to adversarial attacks exhibit more interpretable saliency maps than their non-robust counterparts. We aim to quantify this…

Machine Learning · Statistics 2019-05-13 Christian Etmann , Sebastian Lunz , Peter Maass , Carola-Bibiane Schönlieb

Woven fabrics play an essential role in everyday textiles for clothing/sportswear, water filtration, and retaining walls, to reinforcements in stiff composites for lightweight structures like aerospace, sporting, automotive, and marine…

Applied Physics · Physics 2023-11-27 Haotian Feng , Sabarinathan P Subramaniyan , Hridyesh Tewani , Pavana Prabhakar

Lightning plays a crucial role in the Earth's climate system, yet existing parameterizations for use in forecasting and earth system models show room for improvement in capturing spatial and temporal variations in its frequency. This study…

Atmospheric and Oceanic Physics · Physics 2025-09-15 Randall Jones , Joel A. Thornton , Chris J. Wright , Robert Holzworth

A neural network architecture is presented that exploits the multilevel properties of high-dimensional parameter-dependent partial differential equations, enabling an efficient approximation of parameter-to-solution maps, rivaling…

Machine Learning · Computer Science 2024-08-21 Janina Enrica Schütte , Martin Eigel

In this paper we generalize correspondence theorems of Mikhalkin and Nishinou-Siebert providing a correspondence between algebraic and parameterized tropical curves. We also give a description of a canonical tropicalization procedure for…

Algebraic Geometry · Mathematics 2011-07-12 Ilya Tyomkin

We define the tropical moduli space of covers of a tropical line in the plane as weighted abstract polyhedral complex, and the tropical branch map recording the images of the simple ramifications. Our main result is the invariance of the…

Algebraic Geometry · Mathematics 2013-10-29 Arne Buchholz , Hannah Markwig

Adversarial attacks have been proven to be potential threats to Deep Neural Networks (DNNs), and many methods are proposed to defend against adversarial attacks. However, while enhancing the robustness, the clean accuracy will decline to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Xingxing Wei , Shiji Zhao , Bo li

We introduce the first graph kernels for metric graphs via tropical algebraic geometry. In contrast to conventional graph kernels based on graph combinatorics such as nodes, edges, and subgraphs, our metric graph kernels are purely based on…

Machine Learning · Computer Science 2026-01-30 Yueqi Cao , Anthea Monod
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