差分

このページの2つのバージョン間の差分を表示します。

--- en:intro:publications [2025/09/01 18:31] – [Conference Activities & Talks] Naoki SATO
+++ en:intro:publications [2025/09/09 17:59] (現在) – Naoki SATO
@@ 行 11: / 行 11: @@
 ==== Proceedings ====
-  - [[https://scholar.google.co.jp/citations?user=rNbGTIgAAAAJ&hl=ja|Naoki Sato]], [[..:iiduka:|Hideaki Iiduka]]: **[[https://ojs.aaai.org/index.php/AAAI/article/view/34234|Explicit and Implicit Graduated Optimization in Deep Neural Networks]]**, [[https://aaai.org/proceeding/aaai-39-2025/|Proceedings of the AAAI Conference on Artificial Intelligence]], 39 (19), 20283--20291 (2025)
+  - Keisuke Kamo, [[..:iiduka:|Hideaki Iiduka]]: **Increasing Batch Size Improves Convergence of Stochastic Gradient Descent with Momentum**, Proceedings of the 17th Asian Conference on Machine Learning, PMLR ???: ????-???? (2025)
+  - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Oowada]], [[..:iiduka:|Hideaki Iiduka]]: **Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size**, Proceedings of the 17th Asian Conference on Machine Learning, PMLR ???: ????-???? (2025)
+  - [[https://scholar.google.com/citations?user=hdDU4Z4AAAAJ&hl=ja|Kento Imaizumi]], [[..:iiduka:|Hideaki Iiduka]]: **Both Asymptotic and Non-Asymptotic Convergence of Quasi-Hyperbolic Momentum using Increasing Batch Size**, Proceedings of the 17th Asian Conference on Machine Learning, PMLR ???: ????-???? (2025)
+  - [[https://scholar.google.co.jp/citations?user=rNbGTIgAAAAJ&hl=ja|Naoki Sato]], [[..:iiduka:|Hideaki Iiduka]]: **[[https://ojs.aaai.org/index.php/AAAI/article/view/34234|Explicit and Implicit Graduated Optimization in Deep Neural Networks]]**, [[https://aaai.org/proceeding/aaai-39-2025/|Proceedings of the AAAI Conference on Artificial Intelligence]], 39 (19), 20283--20291 (2025) [[https://ojs.aaai.org/index.php/AAAI/article/view/34234|Open Access]]
 ==== Reward and Punishment ====
@@ 行 19: / 行 22: @@
 ==== Conference Activities & Talks ====
   - Keisuke Kamo, [[..:iiduka:|Hideaki Iiduka]]: **Increasing Batch Size Improves Convergence of Stochastic Gradient Descent with Momentum**, [[https://www.acml-conf.org/2025/|The 17th Asian Conference on Machine Learning (ACML2025)]], Taipei, Taiwan (Dec. 9--12, 2025)
-  - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Oowada]], [[..:iiduka:|Hideaki Iiduka]]: **Increasing Batch Size Improves Convergence of Stochastic Gradient Descent with Momentum**, [[https://www.acml-conf.org/2025/|The 17th Asian Conference on Machine Learning (ACML2025)]], Taipei, Taiwan (Dec. 9--12, 2025)
+  - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Oowada]], [[..:iiduka:|Hideaki Iiduka]]: **Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size**, [[https://www.acml-conf.org/2025/|The 17th Asian Conference on Machine Learning (ACML2025)]], Taipei, Taiwan (Dec. 9--12, 2025)
   - [[https://scholar.google.com/citations?user=hdDU4Z4AAAAJ&hl=ja|Kento Imaizumi]], [[..:iiduka:|Hideaki Iiduka]]: **Both Asymptotic and Non-Asymptotic Convergence of Quasi-Hyperbolic Momentum using Increasing Batch Size**, [[https://www.acml-conf.org/2025/|The 17th Asian Conference on Machine Learning (ACML2025)]], Taipei, Taiwan (Dec. 9--12, 2025)
-  - [[https://scholar.google.co.jp/citations?user=rNbGTIgAAAAJ&hl=ja|Naoki Sato]], [[en:iiduka:|Hideaki Iiduka]]: **Analysis of Muon's convergence and critical batch size**, The 2025 Fall National Conference of Operations Research Society of Japan, Higashi-Hiroshima campus, Hiroshima University (Sep. 12, 2025)
+  - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Oowada]], [[..:iiduka:|Hideaki Iiduka]]: **Improvements of Computational Eﬃciency and Convergence Rate of Riemannian Stochastic Gradient Descent with Increasing Batch Size**, RIMS Workshop on Nonlinear Analysis and Convex Analysis, Research Institute for Mathematical Sciences, Kyoto University (Sep. 26, 2025)
+  - [[https://scholar.google.co.jp/citations?user=rNbGTIgAAAAJ&hl=ja|Naoki Sato]], [[https://scholar.google.co.jp/citations?user=xx7O2voAAAAJ&hl=ja|Hiroki Naganuma]], [[en:iiduka:|Hideaki Iiduka]]: **Analysis of Muon's convergence and critical batch size**, The 2025 Fall National Conference of Operations Research Society of Japan, Higashi-Hiroshima campus, Hiroshima University (Sep. 12, 2025)
   - [[https://scholar.google.co.jp/citations?user=RXrwOgoAAAAJ&hl=ja|Hiroyuki Sakai]], [[en:iiduka:|Hideaki Iiduka]]: **A General Framework of Riemannian Adaptive Optimization Methods with a Convergence Analysis**, The 2025 Fall National Conference of Operations Research Society of Japan, Higashi-Hiroshima campus, Hiroshima University (Sep. 12, 2025)
   - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Owada]], [[..:iiduka:|Hideaki Iiduka]]: **Improving Computational Efficiency and Convergence Rate of Stochastic Gradient Descent on Riemannian Manifolds by Focusing on Batch Size**, Summer School on Continuous Optimization and Related Fields, The Institute of Statistical Mathematics (Aug. 28, 2025)
   - [[https://scholar.google.com/citations?hl=ja&user=s9l7NM8AAAAJ|Hikaru Umeda]], [[..:iiduka:|Hideaki Iiduka]]: **Acceleration of Stochastic Gradient Descent by Increasing Batch Size and Learning Rate**, The 2025 Spring National Conference of Operations Research Society of Japan, Seikei University (Mar. 6, 2025)
-  - Kanata Owada, [[..:iiduka:|Hideaki Iiduka]]: **Batch Size and Learning Rate of Stochastic Gradient Descent on Riemannian manifold**, The 2025 Spring National Conference of Operations Research Society of Japan, Seikei University (Mar. 6, 2025)
+  - [[https://scholar.google.co.jp/citations?hl=ja&user=dejA0qcAAAAJ|Kanata Owada]], [[..:iiduka:|Hideaki Iiduka]]: **Batch Size and Learning Rate of Stochastic Gradient Descent on Riemannian manifold**, The 2025 Spring National Conference of Operations Research Society of Japan, Seikei University (Mar. 6, 2025)
   - [[https://scholar.google.com/citations?user=hdDU4Z4AAAAJ&hl=ja|Kento Imaizumi]], [[..:iiduka:|Hideaki Iiduka]]: **Convergence Analysis of SGD with Momentum with Increasing or Decaying Momentum Factor in Nonconvex Optimization**, The 2025 Spring National Conference of Operations Research Society of Japan, Seikei University (Mar. 6, 2025)
   - [[https://scholar.google.co.jp/citations?user=rNbGTIgAAAAJ&hl=ja|Naoki Sato]], [[en:iiduka:|Hideaki Iiduka]]: **Stochastic Frank Wolfe method for Constrained Nonconvex Optimization and its Application for Adversarial Attack**, The 2025 Spring National Conference of Operations Research Society of Japan, Seikei University (Mar. 6, 2025)