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C O N T R I B U T O R S : R A M A N
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44 Basics of generalization theory
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612 Representation Learning 11113 E
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810.2 Autoencoder defined using a d
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IntroductionThis monograph discusse
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14 theory of deep learning• Train
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2Basics of OptimizationThis chapter
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basics of optimization 19where the
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basics of optimization 21Therefore,
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3Backpropagation and its VariantsTh
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backpropagation and its variants 25
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backpropagation and its variants 27
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backpropagation and its variants 29
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4Basics of generalization theoryGen
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basics of generalization theory 33p
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basics of generalization theory 35w
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basics of generalization theory 37N
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6Algorithmic RegularizationLarge sc
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algorithmic regularization 43minimi
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algorithmic regularization 45update
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algorithmic regularization 476.2 Ma
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algorithmic regularization 496.3.2
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algorithmic regularization 51Given
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algorithmic regularization 53to the
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algorithmic regularization 55Since
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58 theory of deep learning7.1 Preli
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60 theory of deep learningcreasing
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- Page 81 and 82: 9Inductive Biases due to Algorithmi
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- Page 103 and 104: 10Unsupervised learning: OverviewMu
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- Page 111: 11Generative Adversarial NetsChapte
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