Playing hard exploration games by watching YouTube
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[1] J. Schmee. An Introduction to Multivariate Statistical Analysis , 1986 .
[2] Anja Vogler,et al. An Introduction to Multivariate Statistical Analysis , 2004 .
[3] Pieter Abbeel,et al. Apprenticeship learning via inverse reinforcement learning , 2004, ICML.
[4] Anind K. Dey,et al. Maximum Entropy Inverse Reinforcement Learning , 2008, AAAI.
[5] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[6] Brett Browning,et al. A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..
[7] Richard L. Lewis,et al. Where Do Rewards Come From , 2009 .
[8] Trevor Darrell,et al. Deep Domain Confusion: Maximizing for Domain Invariance , 2014, CVPR 2014.
[9] Antonio Torralba,et al. Anticipating the future by watching unlabeled video , 2015, ArXiv.
[10] Bolei Zhou,et al. Object Detectors Emerge in Deep Scene CNNs , 2014, ICLR.
[11] Marc G. Bellemare,et al. The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract) , 2012, IJCAI.
[12] Alexei A. Efros,et al. Unsupervised Visual Representation Learning by Context Prediction , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[13] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[14] Alexei A. Efros,et al. Learning Dense Correspondence via 3D-Guided Cycle Consistency , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Stefano Ermon,et al. Generative Adversarial Imitation Learning , 2016, NIPS.
[16] Tom Schaul,et al. Dueling Network Architectures for Deep Reinforcement Learning , 2015, ICML.
[17] Tom Schaul,et al. Unifying Count-Based Exploration and Intrinsic Motivation , 2016, NIPS.
[18] Traian Rebedea,et al. Playing Atari Games with Deep Reinforcement Learning and Human Checkpoint Replay , 2016, ArXiv.
[19] Alexei A. Efros,et al. Colorful Image Colorization , 2016, ECCV.
[20] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[21] Andrew Owens,et al. Ambient Sound Provides Supervision for Visual Learning , 2016, ECCV.
[22] Marc G. Bellemare,et al. The Reactor: A Sample-Efficient Actor-Critic Architecture , 2017, ArXiv.
[23] Martin A. Riedmiller,et al. Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards , 2017, ArXiv.
[24] Alexei A. Efros,et al. Curiosity-Driven Exploration by Self-Supervised Prediction , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[25] Pieter Abbeel,et al. Third-Person Imitation Learning , 2017, ICLR.
[26] Sergey Levine,et al. One-Shot Visual Imitation Learning via Meta-Learning , 2017, CoRL.
[27] Antonio Torralba,et al. See, Hear, and Read: Deep Aligned Representations , 2017, ArXiv.
[28] Anca D. Dragan,et al. Inverse Reward Design , 2017, NIPS.
[29] Marcin Andrychowicz,et al. One-Shot Imitation Learning , 2017, NIPS.
[30] Andrew Zisserman,et al. Multi-task Self-Supervised Visual Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[31] Sergey Levine,et al. Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[32] Andrew Zisserman,et al. Look, Listen and Learn , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[33] Marc G. Bellemare,et al. A Distributional Perspective on Reinforcement Learning , 2017, ICML.
[34] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[35] Tom Schaul,et al. Rainbow: Combining Improvements in Deep Reinforcement Learning , 2017, AAAI.
[36] Vladlen Koltun,et al. Semi-parametric Topological Memory for Navigation , 2018, ICLR.
[37] David Budden,et al. Distributed Prioritized Experience Replay , 2018, ICLR.
[38] Sergey Levine,et al. Time-Contrastive Networks: Self-Supervised Learning from Video , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[39] Sergio Gomez Colmenarejo,et al. One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL , 2018, ArXiv.
[40] Sergey Levine,et al. Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[41] Shane Legg,et al. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures , 2018, ICML.
[42] George Trigeorgis,et al. Deep Canonical Time Warping for Simultaneous Alignment and Representation Learning of Sequences , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] Jitendra Malik,et al. Zero-Shot Visual Imitation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[44] Antonio Torralba,et al. Cross-Modal Scene Networks , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[46] Rémi Munos,et al. Observe and Look Further: Achieving Consistent Performance on Atari , 2018, ArXiv.
[47] Peter Stone,et al. Behavioral Cloning from Observation , 2018, IJCAI.
[48] Matthew W. Hoffman,et al. Distributed Distributional Deterministic Policy Gradients , 2018, ICLR.
[49] Tom Schaul,et al. Deep Q-learning From Demonstrations , 2017, AAAI.
[50] Sergey Levine,et al. One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning , 2018, Robotics: Science and Systems.
[51] Zheng Wen,et al. Deep Exploration via Randomized Value Functions , 2017, J. Mach. Learn. Res..