2 papers
cs.LG2026
Pruning Binarized Neural Networks: A Dedicated Framework and Globally Weighted Algorithms
Roan Rubiales, Jean Pierre David
Extreme compression of deep neural networks, up to full binarization, dramatically reduces memory footprint and arithmetic complexity, facilitating deployment on constrained edge h…
cs.LG2026
Threshold-Based Early Stopping of Accumulations in Neural Networks with Binary Activation
Quentin Luquet de Saint-Germain, Massil Ait Abdeslam, Jean Pierre David
Binary neural networks are very attractive for constrained deployment, enabling small footprint and low-power inference. For binary activations, the dot products become sign-contro…