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cs.LG2024
FFCL: Forward-Forward Net with Cortical Loops, Training and Inference on Edge Without Backpropagation
Ali Karkehabadi, Houman Homayoun, Avesta Sasan
The Forward-Forward Learning (FFL) algorithm is a recently proposed solution for training neural networks without needing memory-intensive backpropagation. During training, labels…
cs.LG2022
Adaptive-Gravity: A Defense Against Adversarial Samples
Ali Mirzaeian, Zhi Tian, Sai Manoj P D +4
This paper presents a novel model training solution, denoted as Adaptive-Gravity, for enhancing the robustness of deep neural network classifiers against adversarial examples. We c…