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Whats true for Min-max learning?

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Whats true for Min-max learning?

(a) logical And & Or operations are used for input output relations

(b) weight corresponds to minimum & maximum  of units are connected

(c) weights are expressed as linear combination of orthogonal basis vectors

(d) change in weight uses a weighted sum of changes in past input values

The question was asked during an online interview.

My question is taken from Learning Laws in division Activation and Synaptic Dynamics of Neural Networks

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Right choice is (b) weight corresponds to minimum & maximum  of units are connected

The explanation: Min-max learning involves weights which  corresponds to minimum & maximum  of units connected.

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