暂无分享,去创建一个
Philip Bachman | Joelle Pineau | Peter Henderson | Doina Precup | David Meger | Riashat Islam | Doina Precup | Joelle Pineau | Riashat Islam | Peter Henderson | Philip Bachman | D. Meger
[1] S. T. Buckland,et al. An Introduction to the Bootstrap , 1994 .
[2] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[3] Yishay Mansour,et al. Policy Gradient Methods for Reinforcement Learning with Function Approximation , 1999, NIPS.
[4] K. Yuan,et al. Bootstrap approach to inference and power analysis based on three test statistics for covariance structure models. , 2003, The British journal of mathematical and statistical psychology.
[5] Remco R. Bouckaert,et al. Estimating replicability of classifier learning experiments , 2004, ICML.
[6] Eibe Frank,et al. Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms , 2004, PAKDD.
[7] Yoshua Bengio,et al. Inference for the Generalization Error , 1999, Machine Learning.
[8] M. Kenward,et al. An Introduction to the Bootstrap , 2007 .
[9] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[10] Shimon Whiteson,et al. Protecting against evaluation overfitting in empirical reinforcement learning , 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).
[11] Raul H. C. Lopes,et al. Pengaruh Latihan Small Sided Games 4 Lawan 4 Dengan Maksimal Tiga Sentuhan Terhadap Peningkatan VO2MAX Pada Siswa SSB Tunas Muda Bragang Klampis U-15 , 2022, Jurnal Ilmiah Mandala Education.
[12] Jens Wawerla,et al. Publishing Identifiable Experiment Code And Configuration Is Important, Good and Easy , 2012, ArXiv.
[13] Kiri Wagstaff,et al. Machine Learning that Matters , 2012, ICML.
[14] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[15] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.
[16] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[17] Anne-Laure Boulesteix,et al. A Plea for Neutral Comparison Studies in Computational Sciences , 2012, PloS one.
[18] Brigid Wilson,et al. Implementing Reproducible Research , 2014 .
[19] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[20] Xavier Bouthillier,et al. Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets , 2014, NIPS.
[21] Tianqi Chen,et al. Empirical Evaluation of Rectified Activations in Convolutional Network , 2015, ArXiv.
[22] Philip S. Thomas,et al. High-Confidence Off-Policy Evaluation , 2015, AAAI.
[23] Zoran Popovic,et al. Offline Evaluation of Online Reinforcement Learning Algorithms , 2016, AAAI.
[24] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[25] Pieter Abbeel,et al. Benchmarking Deep Reinforcement Learning for Continuous Control , 2016, ICML.
[26] David Silver,et al. Learning values across many orders of magnitude , 2016, NIPS.
[27] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[28] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[29] Sergey Levine,et al. High-Dimensional Continuous Control Using Generalized Advantage Estimation , 2015, ICLR.
[30] Hugo Gimbert,et al. Online Reinforcement Learning for Real-Time Exploration in Continuous State and Action Markov Decision Processes , 2016, ArXiv.
[31] Philip S. Thomas,et al. Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning , 2016, ICML.
[32] Wojciech Zaremba,et al. OpenAI Gym , 2016, ArXiv.
[33] Elman Mansimov,et al. Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation , 2017, NIPS.
[34] Pieter Abbeel,et al. Third-Person Imitation Learning , 2017, ICLR.
[35] Sergey Levine,et al. Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic , 2016, ICLR.
[36] Tom Schaul,et al. StarCraft II: A New Challenge for Reinforcement Learning , 2017, ArXiv.
[37] Richard E. Turner,et al. Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning , 2017, NIPS.
[38] Luiz Chaimowicz,et al. MOBA: a New Arena for Game AI , 2017, ArXiv.
[39] Sham M. Kakade,et al. Towards Generalization and Simplicity in Continuous Control , 2017, NIPS.
[40] Peter Henderson,et al. Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control , 2017, ArXiv.
[41] Alec Radford,et al. Proximal Policy Optimization Algorithms , 2017, ArXiv.
[42] Marcin Andrychowicz,et al. Parameter Space Noise for Exploration , 2017, ICLR.
[43] Marlos C. Machado,et al. Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents , 2017, J. Artif. Intell. Res..