Jul 15, 2020 · Our framework specializes to the convolutional dictionary learning problem when we consider integer shifts. Using properties of positive ...

Jun 30, 2021 · Our framework specializes to the convolutional dictionary learning problem when we consider integer shifts. Using properties of positive ...

This work develops a framework for learning dictionaries for data under the constraint that the collection of basic building blocks remains invariant under ...

Jul 25, 2023 · In this paper, we study the problem of learning a dictionary invariant to a pre-specified group of symmetries through the lens of ...

May 31, 2023 · In this paper, we examine the problem of learning a dictionary that is invariant under a pre-specified group of transformations. Natural ...

Sparse dictionary learning is a representation learning method which aims at finding a sparse representation of the input data in the form of a linear ...

Abstract—In this letter we give efficient solutions to the con- struction of structured dictionaries for sparse representations. We study circulant and ...

Feb 19, 2021 · Question:how can we exploit group invariance to design more efficient and accurate machine learning algorithms? We shall focus on the case ℐ ⊂ ...

ABSTRACT. Shift-invariant dictionaries are generated by taking all the possible shifts of a few short patterns. They are helpful to represent long.

Complete Dictionary Learning over the Orthogonal Group. (a) n = 50 ... Proof As our objective function is invariant under signed permutation group, without.