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- W2105616081 abstract "We propose a biologically plausible learning scheme which enables a system to classify patterns based on the presentation of one single example. During a learning mode, the system recognizes whether a category for a presented pattern has been instantiated before, or whether it must be classified as unknown. In this case a new category is created autonomously. The proposed “one-shot” learning rules are characterized by certain time scale relations between system parameter dynamics and input dynamics. We show that reversing these relations (leading to a statistical learning regime, the learning dynamics can be reduced to a Kohonen learning scheme. Our results show that both “one-shot” and statistical learning in biological systems might be governed by identical laws." @default.
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- W2105616081 date "1997-01-01" @default.
- W2105616081 modified "2023-09-24" @default.
- W2105616081 title "Relative time scales in the self-organization of pattern classification: From “one-shot” to statistical learning" @default.
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- W2105616081 doi "https://doi.org/10.1007/bfb0020164" @default.
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