Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks
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[1] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[2] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Gerald Tesauro,et al. Comparison training of chess evaluation functions , 2001 .
[4] Andrew Tridgell,et al. Learning to Play Chess Using Temporal Differences , 2000, Machine Learning.
[5] Demis Hassabis,et al. Mastering the game of Go without human knowledge , 2017, Nature.
[6] Xiaoou Tang,et al. Facial Landmark Detection by Deep Multi-task Learning , 2014, ECCV.
[7] Murray Campbell,et al. Deep Blue , 2002, Artif. Intell..
[8] Raymond Y. K. Lau,et al. Least Squares Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[9] Yanjun Qi,et al. Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently , 2017, ArXiv.
[10] Michael Buro,et al. From Simple Features to Sophisticated Evaluation Functions , 1998, Computers and Games.
[11] Nathan S. Netanyahu,et al. DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess , 2016, ICANN.
[12] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[13] Tomoyuki Kaneko,et al. Large-Scale Optimization for Evaluation Functions with Minimax Search , 2014, J. Artif. Intell. Res..
[14] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[15] Gerald Tesauro,et al. Connectionist Learning of Expert Preferences by Comparison Training , 1988, NIPS.
[16] Anders Krogh,et al. A Simple Weight Decay Can Improve Generalization , 1991, NIPS.
[17] Matthew Lai,et al. Giraffe: Using Deep Reinforcement Learning to Play Chess , 2015, ArXiv.
[18] Lukasz Kaiser,et al. One Model To Learn Them All , 2017, ArXiv.
[19] Tomoyuki Kaneko,et al. Imitation Learning for Playing Shogi Based on Generative Adversarial Networks , 2017, 2017 Conference on Technologies and Applications of Artificial Intelligence (TAAI).
[20] Demis Hassabis,et al. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm , 2017, ArXiv.