This work proposes a flattening methodology that preserves GHRR's matrix-based encoding while executing training and inference directly in vector space, functionally equivalent to FHRR inference yet free of permutation logic.
William Youngwoo Chung, Hyunwoo Oh, Calvin Yeung et al.· International Symposium on L...· 0 citations
Across CIFAR10, COIL100, and ETH80 under FGSM and Genetic Attack, ViT + Classical HDC degrades more gracefully than Pure HDC and ViT + HDC baselines, and achieves higher normalized AURC, lower attack-time decision margins, and larger gains from partial adversarial retraining.
Hamza Errahmouni Barkam, Salaar Saraj, Zhen Ye et al.· International Symposium on L...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.