研究概要

主要論文

• 1. Taiji Suzuki, Hiroshi Abe, Tomoya Murata, Shingo Horiuchi, Kotaro Ito, Tokuma Wachi, So Hirai, Masatoshi Yukishima, Tomoaki Nishimura.:
  "Spectral pruning: Compressing deep neural networks via spectral analysis and its generalization error"
  The 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020).
• 2. Taiji Suzuki, Hiroshi Abe, Tomoaki Nishimura.:
  "Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network"
  The 8th International Conference on Learning Representations (ICLR 2020).
• 3. Jimmy Ba, Murat Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang.:
  "Generalization of two-layer neural networks: An asymptotic viewpoint"
  The 8th International Conference on Learning Representations (ICLR 2020).
• 4. Kenta Oono and Taiji Suzuki.:
  "Approximation and non-parametric estimation of ResNet-type convolutional neural networks"
  The 36th International Conference on Machine Learning (ICML 2019), pp. 4922-4931, (2019).
• 5. Taiji Suzuki.:
  "Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality"
  The 7th International Conference on Learning Representations (ICLR 2019).
• 6. Atsushi Nitanda and Taiji Suzuki.:
  "Functional gradient boosting based on residual network perception"
  The 36th International Conference on Machine Learning (ICML 2018), pp. 3819-3828, (2018).
• 7. Taiji Suzuki.:
  "Fast generalization error bound of deep learning from a kernel perspective"
  The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), pp. 1397-1406, (2018).
• 8. Suzuki, T., Kanagawa, H., Kobayashi, H., Shimizu, N., and Tagami, Y.:
  "Minimax optimal alternating minimization for kernel nonparametric tensor learning"
  The 30th Annual Conference on Neural Information Processing Systems (NIPS2016), pp. 3783-3791, (2016).

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