A machine-learning technique in which a smaller, simpler AI model (the “student”) is trained to mimic the behavior and outputs of a larger, more complex model (the “teacher”). The goal is to retain much of the teacher’s performance while making the student faster and cheaper to run.
Explore Similar Terms:
Adversarial Distillation Attack | Fine-tuning | Machine Learning | Transfer Learning
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