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Discrimination Learning

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Statistical learning of parts and wholes: A neural network approach.

Journal of experimental psychology. General
Statistical learning is often considered to be a means of discovering the units of perception, such as words and objects, and representing them as explicit "chunks." However, entities are not undifferentiated wholes but often contain parts that contr...

Discriminative margin-sensitive autoencoder for collective multi-view disease analysis.

Neural networks : the official journal of the International Neural Network Society
Medical prediction is always collectively determined based on bioimages collected from different sources or various clinical characterizations described from multiple physiological features. Notably, learning intrinsic structures from multiple hetero...

A Predictive-Coding Network That Is Both Discriminative and Generative.

Neural computation
Predictive coding (PC) networks are a biologically interesting class of neural networks. Their layered hierarchy mimics the reciprocal connectivity pattern observed in the mammalian cortex, and they can be trained using local learning rules that appr...

An exploration of error-driven learning in simple two-layer networks from a discriminative learning perspective.

Behavior research methods
Error-driven learning algorithms, which iteratively adjust expectations based on prediction error, are the basis for a vast array of computational models in the brain and cognitive sciences that often differ widely in their precise form and applicati...