Naganuma, Hiroki

12 publications

TMLR 2025 An Empirical Study of Pre-Trained Model Selection for Out-of-Distribution Generalization and Calibration Hiroki Naganuma, Ryuichiro Hataya, Kotaro Yoshida, Ioannis Mitliagkas

ICLR 2025 Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian McAuley, Hiroki Naganuma

TMLR 2025 Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training Hiroki Naganuma, Xinzhi Zhang, Man-Chung Yue, Ioannis Mitliagkas, Russell J. Hewett, Philipp Andre Witte, Yin Tat Lee

NeurIPSW 2024 Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian McAuley, Hiroki Naganuma

ICML 2024 No Wrong Turns: The Simple Geometry of Neural Networks Optimization Paths Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras, Ioannis Mitliagkas

NeurIPSW 2024 Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training Hiroki Naganuma, Xinzhi Zhang, Man-Chung Yue, Ioannis Mitliagkas, Russell J. Hewett, Philipp Andre Witte, Yin Tat Lee

ICLRW 2024 Smoothness-Adaptive Sharpness-Aware Minimization for Finding Flatter Minima Hiroki Naganuma, Junhyung Lyle Kim, Anastasios Kyrillidis, Ioannis Mitliagkas

TMLR 2024 Towards Understanding Variants of Invariant Risk Minimization Through the Lens of Calibration Kotaro Yoshida, Hiroki Naganuma

AISTATS 2023 Conjugate Gradient Method for Generative Adversarial Networks Hiroki Naganuma, Hideaki Iiduka

TMLR 2023 Empirical Study on Optimizer Selection for Out-of-Distribution Generalization Hiroki Naganuma, Kartik Ahuja, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato, Ioannis Mitliagkas

NeurIPSW 2022 Empirical Study on Optimizer Selection for Out-of-Distribution Generalization Hiroki Naganuma, Kartik Ahuja, Ioannis Mitliagkas, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato

CoLLAs 2022 Optimal Transport Meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation Kilian Fatras, Hiroki Naganuma, Ioannis Mitliagkas