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cs.LG2026
Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis
Pedram Bakhtiarifard, Sophia N. Wilson, Mahmoud Afifi +2
Training large-scale deep neural networks (DNNs) is resource-intensive, making model compression a practical necessity. The widely accepted ''learning as compression'' hypothesis p…
cs.LG2024
Small Contributions, Small Networks: Efficient Neural Network Pruning Based on Relative Importance
Mostafa Hussien, Mahmoud Afifi, Kim Khoa Nguyen +1
Recent advancements have scaled neural networks to unprecedented sizes, achieving remarkable performance across a wide range of tasks. However, deploying these large-scale models o…