AI engineering glossary · Linear algebra
What is infinity norm?
Infinity norm (also called Max norm, Chebyshev norm): The size of a vector defined as the largest absolute value among its components. It is the limit of the Lp family as p grows and is used to bound the worst-case error in any single coordinate, for example in gradient clipping.
Infinity norm: an example
||[3, -7, 2]||_inf = 7.
Related terms
More Linear algebra terms
- Inner product
- Inverse matrix
- Kronecker product
- L1 norm
- L2 norm
- Least squares
- Linear combination
- Linear independence
Where you learn it
Infinity norm is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.