| 2026 | EDBT | Accelerating Graph Construction for MIPS without Search Accuracy Loss. | Yasuhiro Fujiwara, ngel Lpez Garca-Arias, Yu Mitsuzumi, Yasutoshi Ida, Atsutoshi Kumagai, Masahiro Nakano, Makoto Nakatsuji, Akisato Kimura |
| 2026 | KDD | Fast Vector Quantization Algorithm for ScaNN. | Yasuhiro Fujiwara, ngel Lpez Garca-Arias, Yasutoshi Ida, Atsutoshi Kumagai, Masahiro Nakano, Makoto Nakatsuji, Akisato Kimura |
| 2025 | AISTATS | Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion. | Tomoharu Iwata, Atsutoshi Kumagai |
| 2025 | AISTATS | Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression. | Tomoharu Iwata, Atsutoshi Kumagai, Yasutoshi Ida |
| 2025 | AISTATS | Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation. | Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara |
| 2025 | ICLR | Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods. | Akira Ito, Masanori Yamada, Atsutoshi Kumagai |
| 2025 | ICLR | Test-time Adaptation for Regression by Subspace Alignment. | Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami |
| 2025 | ICLR | Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation. | Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita |
| 2025 | ICML | Linear Mode Connectivity between Multiple Models modulo Permutation Symmetries. | Akira Ito, Masanori Yamada, Atsutoshi Kumagai |
| 2025 | ICML | Positive-unlabeled AUC Maximization under Covariate Shift. | Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Kazuki Adachi, Yasuhiro Fujiwara |
| 2024 | AAAI | Zero-Shot Task Adaptation with Relevant Feature Information. | Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara |
| 2024 | GLOBECOM | Partial AUC Maximization for Security Log Analysis Robust to Overfitting and Noisy Labels. | Taishi Nishiyama, Atsutoshi Kumagai, Akinori Fujino, Kazunori Kamiya |
| 2023 | AAAI | Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers. | Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara |
| 2023 | AISTATS | Fast Block Coordinate Descent for Non-Convex Group Regularizations. | Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai |
| 2023 | AISTATS | Meta-learning for Robust Anomaly Detection. | Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara |
| 2023 | DASFAA | Efficient Network Representation Learning via Cluster Similarity. | Yasuhiro Fujiwara, Yasutoshi Ida, Atsutoshi Kumagai, Masahiro Nakano, Akisato Kimura, Naonori Ueda |
| 2023 | ICIP | Covariance-Aware Feature Alignment with Pre-Computed Source Statistics for Test-Time Adaptation to Multiple Image Corruptions. | Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai |
| 2022 | IJCNN | Transfer Anomaly Detection for Maximizing the Partial AUC. | Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama, Yasuhiro Fujiwara |
| 2022 | KDD | Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. | Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima |
| 2021 | AusDM | Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs. | Taishi Nishiyama, Atsutoshi Kumagai, Akinori Fujino, Kazunori Kamiya |
| 2021 | CIKM | Fast and Accurate Anchor Graph-based Label Prediction. | Yasuhiro Fujiwara, Yasutoshi Ida, Atsutoshi Kumagai, Sekitoshi Kanai, Naonori Ueda |
| 2021 | ICDE | Fast Similarity Computation for t-SNE. | Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Naonori Ueda |
| 2021 | IJCNN | Semi-supervised Anomaly Detection on Attributed Graphs. | Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara |
| 2020 | ISCC | SILU: Strategy Involving Large-scale Unlabeled Logs for Improving Malware Detector. | Taishi Nishiyama, Atsutoshi Kumagai, Kazunori Kamiya, Kenji Takahashi |
| 2020 | KDD | Efficient Algorithm for the b-Matching Graph. | Yasuhiro Fujiwara, Atsutoshi Kumagai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda |
| 2019 | AAAI | Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations. | Atsutoshi Kumagai, Tomoharu Iwata |
| 2019 | CIKM | Fast Random Forest Algorithm via Incremental Upper Bound. | Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Junya Arai, Naonori Ueda |
| 2019 | COMPSAC | Alchemy: Stochastic Feature Regeneration for Malicious Network Traffic Classification. | Bo Hu, Atsutoshi Kumagai, Kazunori Kamiya, Kenji Takahashi, Daniel Dalek, Ola Sderstrm, Kazuya Okada, Yuji Sekiya, Akihiro Nakao |
| 2019 | ICDM | Transfer Metric Learning for Unseen Domains. | Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara |
| 2018 | KDD | Learning Dynamics of Decision Boundaries without Additional Labeled Data. | Atsutoshi Kumagai, Tomoharu Iwata |
| 2017 | AAAI | Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance. | Atsutoshi Kumagai, Tomoharu Iwata |
| 2017 | IJCAI | Learning Latest Classifiers without Additional Labeled Data. | Atsutoshi Kumagai, Tomoharu Iwata |
| 2016 | AAAI | Learning Future Classifiers without Additional Data. | Atsutoshi Kumagai, Tomoharu Iwata |