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Use of dropouts and sparsity for regularization of autoencoders in deep neural networks
(Bilkent University, 2015-01)
Deep learning has emerged as an e ective pre-training technique for neural networks with many hidden layers. To overcome the over- tting issue, usually large capacity models are used. In this thesis, two methodologies ...