Learning Deep Architectures for AI

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Glove: Global Vectors for Word Representation→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→Learning Deep Architectures for AILegacy edge — source detail unavailable
• A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Curriculum learning→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→Learning Deep Architectures for AILegacy edge — source detail unavailable
• A random forest guided tour→Learning Deep Architectures for AILegacy edge — source detail unavailable
• The Limitations of Deep Learning in Adversarial Settings→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Machine Learning in Medicine→Learning Deep Architectures for AILegacy edge — source detail unavailable
• A few useful things to know about machine learning→Learning Deep Architectures for AILegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Siamese Neural Networks for One-shot Image Recognition→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep learning for healthcare: review, opportunities and challenges→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→Learning Deep Architectures for AILegacy edge — source detail unavailable
• State-of-the-art in artificial neural network applications: A survey→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Random ForestsLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Support-Vector NetworksLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Learning representations by back-propagating errorsLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Reinforcement Learning: An IntroductionLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Classification and Regression Trees.Legacy edge — source detail unavailable
• Learning Deep Architectures for AI→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Indexing by latent semantic analysisLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Nonlinear Component Analysis as a Kernel Eigenvalue ProblemLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Independent Component AnalysisLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Stacked generalizationLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Introduction to Reinforcement LearningLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Advances in kernel methods: support vector learningLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Understanding the difficulty of training deep feedforward neural networks→Learning representations by back-propagating errorsLegacy 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 unified architecture for natural language processingLegacy 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
• Deep learning in neural networks: An overview→Introduction to Reinforcement LearningLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Independent Component AnalysisLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Advances in kernel methods: support vector learningLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Reinforcement Learning: An IntroductionLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Stacked generalizationLegacy edge — source detail unavailable
• Reducing the Dimensionality of Data with Neural Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Reducing the Dimensionality of Data with Neural Networks→Indexing by latent semantic analysisLegacy edge — source detail unavailable
• Support-Vector Networks→Learning representations by back-propagating errorsLegacy edge — source detail unavailable
• Support-Vector Networks→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
• Nonlinear Component Analysis as a Kernel Eigenvalue Problem→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
• Nonlinear Component Analysis as a Kernel Eigenvalue Problem→Support-Vector NetworksLegacy edge — source detail unavailable
• Nonlinear Component Analysis as a Kernel Eigenvalue Problem→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition→Learning representations by back-propagating errorsLegacy 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→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 unified architecture for natural language processingLegacy 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
• Deep Sparse Rectifier Neural Networks→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
• Deep Sparse Rectifier Neural Networks→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• A few useful things to know about machine learning→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Machine Learning in Medicine→Random ForestsLegacy edge — source detail unavailable
• The Limitations of Deep Learning in Adversarial Settings→Learning representations by back-propagating errorsLegacy edge — source detail unavailable
• The Limitations of Deep Learning in Adversarial Settings→A unified architecture for natural language processingLegacy edge — source detail unavailable
• The Limitations of Deep Learning in Adversarial Settings→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• The Limitations of Deep Learning in Adversarial Settings→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• A random forest guided tour→Random ForestsLegacy edge — source detail unavailable
• A random forest guided tour→Classification and Regression Trees.Legacy edge — source detail unavailable
• Glove: Global Vectors for Word Representation→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Glove: Global Vectors for Word Representation→Indexing by latent semantic analysisLegacy edge — source detail unavailable
• Curriculum learning→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Curriculum learning→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Curriculum learning→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Learning in Medical Image Analysis→Learning representations by back-propagating errorsLegacy 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→Deep learning in neural networks: An overviewLegacy 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 unified architecture for natural language processingLegacy 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→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→Deep learning in neural networks: An overviewLegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→A unified architecture for natural language processingLegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• A survey of deep neural network architectures and their applications→Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech RecognitionLegacy edge — source detail unavailable
• Deep learning for healthcare: review, opportunities and challenges→Learning representations by back-propagating errorsLegacy edge — source detail unavailable
• Deep learning for healthcare: review, opportunities and challenges→Deep learning in neural networks: An overviewLegacy edge — source detail unavailable
• Deep learning for healthcare: review, opportunities and challenges→Reducing the Dimensionality of Data with Neural NetworksLegacy edge — source detail unavailable
• Deep learning for healthcare: review, opportunities and challenges→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→Learning representations by back-propagating errorsLegacy 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→Deep learning in neural networks: An overviewLegacy 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→Deep Sparse Rectifier Neural NetworksLegacy edge — source detail unavailable
• Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• State-of-the-art in artificial neural network applications: A survey→A survey of deep neural network architectures and their applicationsLegacy edge — source detail unavailable
• Random Forests→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures→Learning long-term dependencies with gradient descent is difficultLegacy edge — source detail unavailable
• A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures→Deep Convolutional Neural Networks for Image Classification: A Comprehensive ReviewLegacy edge — source detail unavailable
• Siamese Neural Networks for One-shot Image Recognition→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→A training algorithm for optimal margin classifiersLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→Support-Vector NetworksLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→A Fast Learning Algorithm for Deep Belief NetsLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→Nonlinear Component Analysis as a Kernel Eigenvalue ProblemLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→Random ForestsLegacy edge — source detail unavailable
• Understanding Machine Learning: From Theory To Algorithms→Classification and Regression Trees.Legacy edge — source detail unavailable