Genetic algorithm vs. gradient descent for training a neural network architecture dedicated to low data regimes in small medical datasets

arXiv:2605.27411 · cs.NE, cs.LG · Submitted 2026-05-13 · Read on arXiv

cs.NE, cs.LG

Submitted: 2026-05-13

Updated: 2026-09-17

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Gradient Descent — 17× in this paper
• Accuracy — 10× in this paper · explained in 1 episode
• Genetic Algorithms — 4× in this paper
• Regularization — 4× in this paper · explained in 3 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AI Alignment — 1× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes

Sources

• Scaling Laws for Neural Language Models
• Group Normalization

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