Joint Applied Math Seminar/Harmonic Analysis and
Signal Processing Seminar
Classification
by Invariant Scattering
Stephane Mallat
Ecole Polytechnique
Friday, September 17, 2010, 11:30am, WWH 1302
Abstract
Signal classes are usually invariant to groups of operators such as
translations or scalings, and to larger Lie groups of deformations.
Classification thus requires finding informative invariants. Invariants
are also at the core of quantum physics through Gauge theories. We
introduce non-linear invariant operators, similar to quantum
scattering. These operators have small commutators with elastic
deformations and provide new representations of stationary processes.
Their computational architecture reminds deep neural networks, but
learning is needed at a single layer, and implemented with O(N)
operations. State of the art results are shown for image classification
of deformed patterns and random textures.