On the importance of initialization and momentum in deep learning

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• Adam: A Method for Stochastic Optimization→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Neural Architecture Search with Reinforcement Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Character-level Convolutional Networks for Text Classification→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Boosting Adversarial Attacks with Momentum→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Convolutional Sequence to Sequence Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Deep Speech: Scaling up end-to-end speech recognition→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• Learning Temporal Regularity in Video Sequences→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• An Empirical Exploration of Recurrent Network Architectures→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• A Survey on Deep Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Long Short-Term MemoryLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi…Legacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Neural Networks: Tricks of the TradeLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• On the importance of initialization and momentum in deep learning→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• Adam: A Method for Stochastic Optimization→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Speech: Scaling up end-to-end speech recognition→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• Deep Speech: Scaling up end-to-end speech recognition→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep Speech: Scaling up end-to-end speech recognition→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Acoustic Modeling Using Deep Belief Networks→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Acoustic Modeling Using Deep Belief Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Acoustic Modeling Using Deep Belief Networks→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Long Short-Term Memory→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Reducing the Dimensionality of Data with Neural Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Character-level Convolutional Networks for Text Classification→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Neural Networks for Acoustic Modeling in Speech Recognition→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Deep Speech: Scaling up end-to-end speech recognitionLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin→Deep Neural Networks for Acoustic Modeling in Speech RecognitionLegacy edge — source detail unavailable
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Learning Temporal Regularity in Video Sequences→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
• Learning Temporal Regularity in Video Sequences→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Learning Temporal Regularity in Video Sequences→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Neural Architecture Search with Reinforcement Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Convolutional Sequence to Sequence Learning→Long Short-Term MemoryLegacy edge — source detail unavailable
• Convolutional Sequence to Sequence Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Neural Networks: Tricks of the TradeLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Inception-v4, Inception-ResNet and the Impact of Residual Connections on LearningLegacy edge — source detail unavailable
• Boosting Adversarial Attacks with Momentum→Inception-v4, Inception-ResNet and the Impact of Residual Connections on LearningLegacy edge — source detail unavailable
• A Survey on Deep Learning→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
• A Survey on Deep Learning→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• A Survey on Deep Learning→Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi…Legacy edge — source detail unavailable
• A Survey on Deep Learning→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• A Survey on Deep Learning→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• A Survey on Deep Learning→Character-level Convolutional Networks for Text ClassificationLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→Acoustic Modeling Using Deep Belief NetworksLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→Deep Convolutional Neural Networks for Image Classification: A Comprehensive ReviewLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→Inception-v4, Inception-ResNet and the Impact of Residual Connections on LearningLegacy edge — source detail unavailable
• A State-of-the-Art Survey on Deep Learning Theory and Architectures→An Empirical Exploration of Recurrent Network ArchitecturesLegacy edge — source detail unavailable
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
• An Empirical Exploration of Recurrent Network Architectures→Long Short-Term MemoryLegacy edge — source detail unavailable
• An Empirical Exploration of Recurrent Network Architectures→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• An Empirical Exploration of Recurrent Network Architectures→Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communi…Legacy edge — source detail unavailable