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Lipschitz-based robustness estimation for hyperdimensional learning

With the adoption of machine learning models in various practical domains, there is a growing need for evaluating and increasing model robustness. Hyperdimensional computing (HDC) is a neurosymbolic computational paradigm that represents symbols as high dimensional vectors and symbolic operations as...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Calvin Yeung, Hamza Errahmouni Barkam, Zhuowen Zou, Sanggeon Yun, Nathaniel D. Bastian, Mohsen Imani
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2025-09-01
Schriftenreihe:Frontiers in Artificial Intelligence
Schlagworte:
hyperdimensional computing
vector symbolic architectures
robustness
adversarial attacks
classification
Online-Zugang:https://www.frontiersin.org/articles/10.3389/frai.2025.1637105/full
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