scholar.google.com › citations
A redundancy reduction strategy, which can be applied in stages, is proposed as a way to learn as efficiently as possible the statistical properties of an ensemble of sensory messages.
The precise meaning of redundancy reduction here is a transformation which increases the learning measure L, to be defined in Section 2. Page 3. Redundancy ...
Mar 1, 1993 · A redundancy reduction strategy, which can be applied in stages, is proposed as a way to learn as efficiently as possible the statistical ...
The precise meaning of redundancy reduction here is a transformation which increases the learning measure L, to be defined in Section 2. Page 3. Redundancy ...
A redundancy reduction strategy, which can be applied in stages, is proposed as a way to learn as efficiently as possible the statistical properties of an ...
We formulate this novel unsupervised learning paradigm for a linear network. The method converges in the linear case to the principal component transformation.
Feb 16, 2004 · Title, Redundancy reduction as a strategy for unsupervised learning ; Free Keywords ; Description ; Last Modified Date, Feb 16, 2004 10:30:48.
Intuitively, the proposed approach acts as an unsupervised regularizer on top of the encoder providing an extra feedback during the back-propagation to reduce ...
In this paper, we propose a scheme to explicitly penalize feature redundancies in the bottleneck representation.
In this research, we conducted a Systematic Mapping Study (SMS), examining the types of unsupervised algorithms implemented in developed models.