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MEAN FIELD BOLTZMANN AND HOPFTELD NETWORKS
Contrastive Hebbian Learning in the Continuous Hopfield Model
Mean Field Networks that Learn to Discriminate Temporally Distorted Strings
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activation adaptive approximation architecture associative back-propagation behavior cells Cognitive complex compression network computational concept connectionism connections constraints convergence corresponding Cross Entropy dimensional dynamic encoding energy function environment epochs equations evolution evolutionary evolve example feedforward Figure genetic genetic algorithms given gradient descent hidden nodes hidden units Hinton hybrid implementation initial input units iterations layer learning algorithm learning mechanisms learning rate learning rule linear mapping memory method minimize module neural network neuron nonlinear ocular dominance optimal oscillations output units Parallel Distributed Processing parameters past tense pattern performance pole balancing prediction presented problem propagation Q-Learning recurrent network reinforcement reinforcement learning representation represented retinal retrieval robot Rumelhart SAARCS samples segments selection semantic semantic network shows simulations space stems structure supervised learning symbol synapse target task theory tion Touretzky training set University update variables vector verbs vocabulary vowel weights Zipser