両方とも前のリビジョン 前のリビジョン 次のリビジョン | 前のリビジョン 次のリビジョン両方とも次のリビジョン |
en:intro:publications [2021/08/17 11:08] – [Conference Activities & Talks] Hideaki IIDUKA | en:intro:publications [2021/10/14 13:58] – [Publications in Refereed Journals] Hideaki IIDUKA |
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===== 2021 ===== | ===== 2021 ===== |
==== Publications in Refereed Journals ==== | ==== Publications in Refereed Journals ==== |
| - Yini Zhu, [[en:iiduka:|Hideaki Iiduka]]: **Unified Algorithm Framework for Nonconvex Stochastic Optimization in Deep Neural Networks**, [[https://ieeeaccess.ieee.org/|IEEE Access]] (Accepted) (2021) {{:iiduka:final_version.pdf|PDF}} |
| - [[en:iiduka:|Hideaki Iiduka]]: **[[https://ieeexplore.ieee.org/document/9531335|Appropriate Learning Rates of Adaptive Learning Rate Optimization Algorithms for Training Deep Neural Networks]]**, [[https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221036|IEEE Transactions on Cybernetics]] (Accepted) (2021) {{:iiduka:CYB-E-2021-05-1174.pdf|PDF}} |
- Hiroyuki Sakai, [[en:iiduka:|Hideaki Iiduka]]: **[[https://ieeexplore.ieee.org/document/9339934|Riemannian Adaptive Optimization Algorithm and Its Application to Natural Language Processing]]**, [[https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221036|IEEE Transactions on Cybernetics]] (Accepted) (2021) {{:iiduka:CYB-E-2020-04-0756R2.pdf|PDF}} | - Hiroyuki Sakai, [[en:iiduka:|Hideaki Iiduka]]: **[[https://ieeexplore.ieee.org/document/9339934|Riemannian Adaptive Optimization Algorithm and Its Application to Natural Language Processing]]**, [[https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221036|IEEE Transactions on Cybernetics]] (Accepted) (2021) {{:iiduka:CYB-E-2020-04-0756R2.pdf|PDF}} |
- Kazuhiro Hishinuma, [[en:iiduka:|Hideaki Iiduka]]: **Evaluation of Fixed Point Quasiconvex Subgradient Method with Computational Inexactness**, [[http://www.ybook.co.jp/pafa.html|Pure and Applied Functional Analysis]]: Special Issue on Optimization Theory dedicated to Terry Rockafellar on the occasion of his 85th birthday, (2021) (Accepted) {{:iiduka:pafa2020.pdf|PDF}} | - Kazuhiro Hishinuma, [[en:iiduka:|Hideaki Iiduka]]: **Evaluation of Fixed Point Quasiconvex Subgradient Method with Computational Inexactness**, [[http://www.ybook.co.jp/pafa.html|Pure and Applied Functional Analysis]]: Special Issue on Optimization Theory dedicated to Terry Rockafellar on the occasion of his 85th birthday, (2021) (Accepted) {{:iiduka:pafa2020.pdf|PDF}} |
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==== Proceedings ==== | ==== Proceedings ==== |
| - Kanako Shimoyama, [[en:iiduka:|Hideaki Iiduka]]: **Appropriate Gradients Used for Adaptive Learning Rate Optimization Algorithms for Training Deep Neural Networks**, [[https://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/kokyuroku.html|RIMS Kôkyûroku]] [[http://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/contents/2114.html|No.2194]], pp. 1--5, 2021 [[https://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/contents/pdf/2194-01.pdf|Open Access]] |
| - Yini Zhu, Hiroyuki Sakai, [[en:iiduka:|Hideaki Iiduka]]: **Training Neural Networks Using Adaptive Gradient Methods**, [[https://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/kokyuroku.html|RIMS Kôkyûroku]] [[https://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/contents/2194.html|No.2194]], pp. 6--12, 2021 [[https://www.kurims.kyoto-u.ac.jp/~kyodo/kokyuroku/contents/pdf/2194-02.pdf|Open Access]] |
- [[en:iiduka:|Hideaki Iiduka]]: **Halpern-type Subgradient Methods for Convex Optimization over Fixed Point Sets of Nonexpansive Mappings**, Proceedings of International Conference on Nonlinear Analysis and Convex Analysis and International Conference on Optimization: Techniques and Applications -I- pp. 119--125 {{:iiduka:iiduka-naca-icota2019.R1.pdf|PDF}} | - [[en:iiduka:|Hideaki Iiduka]]: **Halpern-type Subgradient Methods for Convex Optimization over Fixed Point Sets of Nonexpansive Mappings**, Proceedings of International Conference on Nonlinear Analysis and Convex Analysis and International Conference on Optimization: Techniques and Applications -I- pp. 119--125 {{:iiduka:iiduka-naca-icota2019.R1.pdf|PDF}} |
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==== Conference Activities & Talks ==== | ==== Conference Activities & Talks ==== |
| - Hiroyuki Sakai, [[:en:iiduka:|Hideaki Iiduka]]: **Riemannian conjugate gradient methods with sufficient descent search directions**, The 2021 Fall National Conference of Operations Research Society of Japan, Kyushu University, Online meeting (Sept. 16, 2021) |
- Koshiro Izumi, [[:en:iiduka:|Hideaki Iiduka]]: **Adaptive scaling conjugate gradient method for neural networks**, RIMS Workshop on Advances in the Theory and Application of Mathematical Optimization, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Aug. 19, 2021) | - Koshiro Izumi, [[:en:iiduka:|Hideaki Iiduka]]: **Adaptive scaling conjugate gradient method for neural networks**, RIMS Workshop on Advances in the Theory and Application of Mathematical Optimization, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Aug. 19, 2021) |
- 京都大学数理解析研究所 共同研究 (公開型) 数理最適化の理論と応用の深化, オンライン開催 (2021年8月19日) | - Yu Kobayashi, [[:en:iiduka:|Hideaki Iiduka]]: **Adaptive conjugate gradient method for deep learning**, The 2021 Spring National Conference of Operations Research Society of Japan, Tokyo Institute of Technology, Online meeting (Mar. 2, 2021) |
- Yu Kobayashi, [[:en:iiduka:|Hideaki Iiduka]]: **Adaptive conjugate gradient method for deep learning**, The 2021 Spring National Conference of Operations Research Society of Japan, Tokyo Institute of Technology, Online meeting (Mar. 2, 2021). | - Hiroyuki Sakai, [[:en:iiduka:|Hideaki Iiduka]]: **Extension of adaptive learning rate optimization algorithms to Riemannian manifolds and its application to natural language processing**, The 2021 Spring National Conference of Operations Research Society of Japan, Tokyo Institute of Technology, Online meeting (Mar. 2, 2021) |
- Hiroyuki Sakai, [[:en:iiduka:|Hideaki Iiduka]]: **Extension of adaptive learning rate optimization algorithms to Riemannian manifolds and its application to natural language processing**, The 2021 Spring National Conference of Operations Research Society of Japan, Tokyo Institute of Technology, Online meeting (Mar. 2, 2021). | |
- Yini Zhu, Hiroyuki Sakai, [[:en:iiduka:|Hideaki Iiduka]]: **Training neural networks using adaptive gradient methods**, RIMS Workshop on Nonlinear Analysis and Convex Analysis, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Mar. 1, 2021) | - Yini Zhu, Hiroyuki Sakai, [[:en:iiduka:|Hideaki Iiduka]]: **Training neural networks using adaptive gradient methods**, RIMS Workshop on Nonlinear Analysis and Convex Analysis, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Mar. 1, 2021) |
- Kanako Shimoyama, Yu Kobayashi, [[:en:iiduka:|Hideaki Iiduka]]: **Appropriate stochastic gradients used in adaptive learning rate optimization algorithms for training deep neural networks**, RIMS Workshop on Nonlinear Analysis and Convex Analysis, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Mar. 1, 2021) | - Kanako Shimoyama, Yu Kobayashi, [[:en:iiduka:|Hideaki Iiduka]]: **Appropriate stochastic gradients used in adaptive learning rate optimization algorithms for training deep neural networks**, RIMS Workshop on Nonlinear Analysis and Convex Analysis, Research Institute for Mathematical Sciences, Kyoto University, Online meeting (Mar. 1, 2021) |