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Abstract : The use of group equivariant operators is becoming more and more important in machine learning and topological data analysis. In this paper we introduce a new method to build G-equivariant non-expansive operators from a set $$\varPhi $$ of bounded and continuous functions $$\varphi :X\rightarrow \mathbb {R}$$ to $$\varPhi $$ itself, where X is a topological space and G is a subgroup of the group of all self-homeomorphisms of X.
https://hal.inria.fr/hal-02060057 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Thursday, March 7, 2019 - 10:37:30 AM Last modification on : Friday, October 30, 2020 - 12:04:04 PM Long-term archiving on: : Saturday, June 8, 2019 - 1:46:01 PM
Francesco Camporesi, Patrizio Frosini, Nicola Quercioli. On a New Method to Build Group Equivariant Operators by Means of Permutants. 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2018, Hamburg, Germany. pp.265-272, ⟨10.1007/978-3-319-99740-7_18⟩. ⟨hal-02060057⟩