Kumagai, Atsutoshi

27 publications

ICLR 2025 Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods Akira Ito, Masanori Yamada, Atsutoshi Kumagai

ECML-PKDD 2025 Fast Proximal Gradient Methods with Node Pruning for Tree-Structured Sparse Regularization Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

AISTATS 2025 Importance-Weighted Positive-Unlabeled Learning for Distribution Shift Adaptation Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara

ICML 2025 Linear Mode Connectivity Between Multiple Models Modulo Permutation Symmetries Akira Ito, Masanori Yamada, Atsutoshi Kumagai

AISTATS 2025 Meta-Learning Task-Specific Regularization Weights for Few-Shot Linear Regression Tomoharu Iwata, Atsutoshi Kumagai, Yasutoshi Ida

AISTATS 2025 Meta-Learning from Heterogeneous Tensors for Few-Shot Tensor Completion Tomoharu Iwata, Atsutoshi Kumagai

ICML 2025 Positive-Unlabeled AUC Maximization Under Covariate Shift Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Kazuki Adachi, Yasuhiro Fujiwara

ICLR 2025 Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita

ICLR 2025 Test-Time Adaptation for Regression by Subspace Alignment Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami

MLJ 2025 Transfer Learning with Pre-Trained Conditional Generative Models Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima

NeurIPS 2024 AUC Maximization Under Positive Distribution Shift Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara

NeurIPS 2024 Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

AAAI 2024 Zero-Shot Task Adaptation with Relevant Feature Information Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

AISTATS 2023 Fast Block Coordinate Descent for Non-Convex Group Regularizations Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai

AAAI 2023 Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara

AISTATS 2023 Meta-Learning for Robust Anomaly Detection Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara

NeurIPS 2023 Regularizing Neural Networks with Meta-Learning Generative Models Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima

NeurIPS 2022 Few-Shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara

NeurIPS 2022 Meta-Ticket: Finding Optimal Subnetworks for Few-Shot Learning Within Randomly Initialized Neural Networks Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida

NeurIPS 2022 Sharing Knowledge for Meta-Learning with Feature Descriptions Tomoharu Iwata, Atsutoshi Kumagai

NeurIPS 2021 Meta-Learning for Relative Density-Ratio Estimation Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

NeurIPS 2020 Meta-Learning from Tasks with Heterogeneous Attribute Spaces Tomoharu Iwata, Atsutoshi Kumagai

NeurIPS 2019 Transfer Anomaly Detection by Inferring Latent Domain Representations Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

AAAI 2019 Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations Atsutoshi Kumagai, Tomoharu Iwata

IJCAI 2017 Learning Latest Classifiers Without Additional Labeled Data Atsutoshi Kumagai, Tomoharu Iwata

AAAI 2017 Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance Atsutoshi Kumagai, Tomoharu Iwata

AAAI 2016 Learning Future Classifiers Without Additional Data Atsutoshi Kumagai, Tomoharu Iwata