H. Khalfi

Deep Neural Network Compression via Data-Driven Low-Rank Singular Value Decomposition

This paper proposes a novel compression method that uses Singular Value Decomposition (SVD) informed by data examples that achieves substantial reductions in model size and computation with minimal impact on accuracy and demonstrates its applicability in compressing deep neural networks to a fraction of their original size.