Slides

論文紹介

  • 2019/07/21のICLR/ICML2019読み会で使用したスライド
  • Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari, Kento Uchida, Shota Saito, and Kouhei Nishida: Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search, Proceedings of the 36th International Conference on Machine Learning (ICML), Vol. 97 of PMLR, pp. 171-180 (2019).
  • http://proceedings.mlr.press/v97/akimoto19a.html
  • 2018/11/27の論文紹介ゼミで使用したスライド(一部改編)
  • K. Kandasamy, W. Neiswanger, J. Schneider, B. Poczos, and E. Xing, “Neural Architecture Search with Bayesian Optimisation and Optimal Transport,” in Proceedings of Thirty-second Conference on Neural Information Processing Systems (NIPS 2018), 2018.
  • https://arxiv.org/abs/1802.07191
  • 2018/10/28のICML2018読み会で使用したスライド
  • H. Cai, J. Yang, W. Zhang, S. Han, and Y. Yu, “Path-Level Network Transformation for Efficient Architecture Search,” in Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 2018, pp. 677–686.
  • http://proceedings.mlr.press/v80/cai18a.html
  • 2018/05/08の論文紹介ゼミで使用したスライド(一部改編)
  • H. Cai, T. Chen, W. Zhang, Y. Yu, and J. Wang, “Efficient Architecture Search by Network Transformation,” in Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2018.
  • https://arxiv.org/abs/1707.04873
  • 2017/10/06の論文紹介ゼミで使用したスライド(一部改編)
  • Z. Xu, G. Huang, K. Q. Weinberger, and A. X. Zheng, “Gradient boosted feature selection”, Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’14, pp. 522-531, 2014.
  • 2017/06/16の論文紹介ゼミで使用したスライド(一部改編)
  • B. Zoph and Q. V Le, “Neural Architecture Search with Reinforcement Learning”, Proceedings of 5th International Conference on Learning Representations (ICLR’17), 2017.
  • 2017/05/12の論文紹介ゼミで使用したスライドです．
  • T. Domhan, J. T. Springenberg, and F. Hutter, “Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves”, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015) (2015)
  • 2016/12/12の論文紹介ゼミで使用したスライド(一部改編)
  • K. He, X. Zhang, S. Ren, and J. Sun, “Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification”, in 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
  • 2016/11/14の論文紹介ゼミで使用したスライド(一部改編)
  • C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra, “Weight Uncertainty in Neural Networks”, Proceedings of the 32nd International Conference on Machine Learning (ICML 2015), May 2015.
  • 2016/09/20の論文紹介ゼミで使用したスライド(一部改編)
  • P. Chaudhari and S. Soatto, “The Effect of Gradient Noise on the Energy Landscape of Deep Networks”, Preprint:arXiv1511.06485v4, Nov. 2015.
  • 2016/07/06の論文紹介ゼミで使用したスライド(一部改編)
  • S. Singh, D. Hoiem, D. Forsyth, “Swapout: Learning an ensemble of deep architectures”, preprint:arXiv, 2016
  • NIPS2016に採択されています． http://papers.nips.cc/paper/6205-swapout-learning-an-ensemble-of-deep-architectures
  • 2016/06/15の論文紹介ゼミで使用したスライド(一部改編)
  • J. Snoek, H. Larochelle, and R. P. Adams, “Practical Bayesian optimization of machine learning algorithms”, Proceedings of Advances in Neural Information Processing Systems 25 (NIPS 2012), pp. 2960–2968 (2012)

イベント発表など

  • 2018/04/13の新ラボ生向けチュートリアルで使用したスライド