soft weight sharing in neural nets
Soft weight sharing is a form of regularization for neural networks where groups of weights are encouraged to have similar values.
This concept has the prerequisites:
Core resources (we're sorry, we haven't finished tracking down resources for this concept yet)
Supplemental resources (the following are optional, but you may find them useful)
→ Pattern Recognition and Machine Learning
A textbook for a graduate machine learning course, with a focus on Bayesian methods.
Location: Section 5.5.7, pages 269-272
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