Searching for "Learning Overcomplete Representations." – sorted by Relevance.
-
Learning Overcomplete Representations
- Learning overcomplete representations Michael S. Lewicki lewicki@(email omitted); Terrence J. Sejnowski
- Cited by 143 (7 self) – Add To MetaCart
-
Learning Nonlinear Overcomplete Representations for Efficient Coding
- Learning nonlinear overcomplete representations for efficient coding Michael S. Lewicki lewicki
- Cited by 30 (6 self) – Add To MetaCart
-
Blind Source Separation of More Sources Than Mixtures Using Overcomplete Representations
- ) learning an overcomplete representation for the observed data and (2) inferring sources given a sparse
- Cited by 64 (2 self) – Add To MetaCart
-
An Information Maximization Approach to Overcomplete and Recurrent Representations
- of another ICA model that can learn overcomplete representations [11]. Our algorithm, however, does not need
- Cited by 4 (2 self) – Add To MetaCart
-
Nonlinear Approaches To Independent Component Analysis
- . In this section, we summarize the method in [11] for learning overcomplete representation that can solve the ICA
- Cited by 3 (0 self) – Add To MetaCart
-
Variational EM algorithms for non-Gaussian latent variable models
- to learning overcomplete representations in [14]. In the integral type of representation, the density p
- Cited by 4 (3 self) – Add To MetaCart
-
A MESSAGE FROM THE EDITOR
- ), “Bayesian Learning with Overcomplete Sets”: In contrast to the orthonormal basis traditionally used
- Add To MetaCart
-
A Generative Model for Separating Illumination and Reflectance from Images
- to learn overcomplete representations of signals (M.S.Lewicki and Sejnowski, 2000). In another version
- Cited by 1 (0 self) – Add To MetaCart

