## AAAI 91 |

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back propagation backpropagation learning beads relative codes Cognitive competitive learning Connectionist Glue curvature data point David Rumelhart desired output energy functions error function experts forward model free parameters gating network gaussian Global method gradient descent H1 units Hand-printed character recognition hidden layer Hidden Markov Model input pattern input units input vector input weights inverse iterative Layers of Shared Learning Algorithm learning procedure learning rate line search linear linearly separable Locally Connected Network log probability minimize network learns Neural Computation Neural Nets Neural Networks non-linear units Number of connections Number of free OOOO OOOO OOOO optimal output units output vector Overfitting Parallel Distributed Processing Performance on test Performance on training phonemes probabilistic interpretation pruning RBF's Real neurons relative to OBF roads SAIC Bomb Detection signal simple snakes speaker speech recognition speed steepest descent subtasks task TDNNs techniques Touretzky training set Translation Invariance Types of Learning Unsupervised learning Waibel weight vector