3 papers
cs.LG2026
Scaling Laws in the Tiny Regime: How Small Models Change Their Mistakes
Mohammed Alnemari, Rizwan Qureshi, Nader Begrazadah
Neural scaling laws describe how model performance improves as a power law with size, but existing work focuses on models above 100M parameters. The sub-20M regime -- where TinyML…
cs.CV2025
Equivariant-Aware Structured Pruning for Efficient Edge Deployment: A Comprehensive Framework with Adaptive Fine-Tuning
Mohammed Alnemari
This paper presents a novel framework combining group equivariant convolutional neural networks (G-CNNs) with equivariant-aware structured pruning to produce compact, transformatio…
eess.SP2022
A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition
Ye Qiao, Mohammed Alnemari, Nader Bagherzadeh
This paper proposes a novel two-stage framework for emotion recognition using EEG data that outperforms state-of-the-art models while keeping the model size small and computational…