Tangent propagation is a way of regularizing neural nets. It encourages the representation to be invariant by penalizing large changes in the representation when small transformations are applied to the inputs.
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 5.5.4, pages 263-265