juniorCurse of Dimensionality
What is over-parameterization in high dimensions?
Updated May 15, 2026
Short answer
When models have more parameters than data points.
Deep explanation
This increases risk of memorization rather than learning general patterns.
Real-world example
Deep networks with millions of parameters.
Common mistakes
- Assuming complexity always improves accuracy.
Follow-up questions
- Why is it still used?
- What controls it?