2 papers
cs.LG2026
Systematic Characterization of Minimal Deep Learning Architectures: A Unified Analysis of Convergence, Pruning, and Quantization
Ziwei Zheng, Huizhi Liang, Vaclav Snasel +4
Deep learning networks excel at classification, yet identifying minimal architectures that reliably solve a task remains challenging. We present a computational methodology for sys…
cs.LG2024
On Learnable Parameters of Optimal and Suboptimal Deep Learning Models
Ziwei Zheng, Huizhi Liang, Vaclav Snasel +4
We scrutinize the structural and operational aspects of deep learning models, particularly focusing on the nuances of learnable parameters (weight) statistics, distribution, node i…