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Presentation_IsabelleLaureyns_Final

Presentation_IsabelleLaureyns_Final - Introduction The...

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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Dynamic Backpropagation ME697Y - Intelligent Systems Isabelle A. G. Laureyns February 2, 2010 1 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Outline 1 Introduction Backpropagation What is Dynamic Backpropagation? 2 The Basic Idea of DBP 3 How DBP works General Setup Equilibrium Points Algorithm 4 Applications 5 Concluding Remarks 6 References 2 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Backpropagation What is Dynamic Backpropagation? Outline 1 Introduction Backpropagation What is Dynamic Backpropagation? 2 The Basic Idea of DBP 3 How DBP works General Setup Equilibrium Points Algorithm 4 Applications 5 Concluding Remarks 6 References 3 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Backpropagation What is Dynamic Backpropagation? Backpropagation Descent in weight space (a) small learning rate - (b) large learning rate - (c) large learning rate and momentum 4 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Backpropagation What is Dynamic Backpropagation? Backpropagation Can be used for training of patterns in recurrent networks Deficiencies: Long training process (result of a non-optimum learning rate or momentum) Some algorithms adapt the learning rate Network paralysis Local minima 5 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Backpropagation What is Dynamic Backpropagation? Network Paralysis Example of network paralysis 6 / 23
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Introduction The Basic Idea of DBP How DBP works Applications Concluding Remarks References Backpropagation What is Dynamic Backpropagation?
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