Human-level control through deep reinforcement learning

References

Page 1

	Year	Citations
ImageNet classification with deep convolutional neural networks Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton Communications of the ACM Convolutional Neural NetworkEngineeringMachine LearningNeural NetworkImagenet Classification	2017	75.5K
Gradient-based learning applied to document recognition Yann LeCun, Léon Bottou, Yoshua Bengio, Proceedings of the IEEE EngineeringMachine LearningMultilayer Neural NetworksImage AnalysisData Science	1998	56.5K
Visualizing Data using t-SNE Laurens van der Maaten, Geoffrey E. Hinton Journal of Machine Learning Research EngineeringData VisualizationData ExplorationVisualization (Data Visualization)Linear Embedding	2008	35.7K
Reinforcement Learning: An Introduction Richard S. Sutton, Andy Barto IEEE Transactions on Neural Networks Artificial IntelligenceEngineeringDeep Reinforcement LearningComputer ScienceRobot Learning	1998	26.8K
Reinforcement Learning: An Introduction IEEE Transactions on Neural Networks Artificial IntelligenceEngineeringDeep Reinforcement LearningStochastic GameGame Theory	2005	25.7K
Reducing the Dimensionality of Data with Neural Networks Geoffrey E. Hinton, Ruslan Salakhutdinov Science	2006	20.5K
Rectified Linear Units Improve Restricted Boltzmann Machines Vinod Nair, Geoffrey E. Hinton International Conference on Machine Learning Convolutional Neural NetworkEngineeringMachine LearningAutoencodersRecurrent Neural Network	2010	13.2K
Learning Deep Architectures for AI Yoshua Bengio Foundations and Trends® in Machine Learning Artificial IntelligenceAi ArchitectureDeep Neural NetworksEngineeringComputer Science	2009	6.8K
Planning and acting in partially observable stochastic domains Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra Artificial Intelligence EngineeringAi PlanningMotion PlanningObservable Stochastic DomainsProbability Theory	1998	4K
Technical Note: Q-Learning Christopher J. Watkins, Peter Dayan Machine Learning	1992	3.6K

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