Atsutoshi Kumagai

According to our database, Atsutoshi Kumagai authored at least 57 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Meta-learning Representations for Learning from Multiple Annotators.

Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama, Yasutoshi Ida, Yasuhiro Fujiwara

CoRR, June, 2025

Transfer learning with pre-trained conditional generative models.

Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima

Mach. Learn., April, 2025

Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation.

Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Test-time Adaptation for Regression by Subspace Alignment.

Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods.

Akira Ito, Masanori Yamada, Atsutoshi Kumagai

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation.

Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression.

Tomoharu Iwata, Atsutoshi Kumagai, Yasutoshi Ida

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion.

Tomoharu Iwata, Atsutoshi Kumagai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Efficient Algorithm for K-Multiple-Means.

Yasuhiro Fujiwara, Atsutoshi Kumagai, Yasutoshi Ida, Masahiro Nakano, Makoto Nakatsuji, Akisato Kimura

Proc. ACM Manag. Data, February, 2024

Meta-learning to calibrate Gaussian processes with deep kernels for regression uncertainty estimation.

Tomoharu Iwata, Atsutoshi Kumagai

Neurocomputing, 2024

Meta-learning for Positive-unlabeled Classification.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

CoRR, 2024

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data.

Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuki Yamanaka

CoRR, 2024

Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching.

Akira Ito, Masanori Yamada, Atsutoshi Kumagai

CoRR, 2024

AUC Maximization under Positive Distribution Shift.

Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations.

Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Partial AUC Maximization for Security Log Analysis Robust to Overfitting and Noisy Labels.

Taishi Nishiyama, Atsutoshi Kumagai, Akinori Fujino, Kazunori Kamiya

Proceedings of the 2024 IEEE Global Communications Conference, 2024

Malicious Log Detection Using Machine Learning to Maximize the Partial AUC.

Taishi Nishiyama, Atsutoshi Kumagai, Akinori Fujino, Kazunori Kamiya

Proceedings of the 21st IEEE Consumer Communications & Networking Conference, 2024

Zero-Shot Task Adaptation with Relevant Feature Information.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Efficient Network Representation Learning via Cluster Similarity.

Yasuhiro Fujiwara, Yasutoshi Ida, Atsutoshi Kumagai, Masahiro Nakano, Akisato Kimura, Naonori Ueda

Data Sci. Eng., September, 2023

Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces.

Tomoharu Iwata, Atsutoshi Kumagai

CoRR, 2023

Regularizing Neural Networks with Meta-Learning Generative Models.

Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Covariance-Aware Feature Alignment with Pre-Computed Source Statistics for Test-Time Adaptation to Multiple Image Corruptions.

Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai

Proceedings of the IEEE International Conference on Image Processing, 2023

Meta-learning for Robust Anomaly Detection.

Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Fast Block Coordinate Descent for Non-Convex Group Regularizations.

Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers.

Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Meta-learning for Out-of-Distribution Detection via Density Estimation in Latent Space.

Tomoharu Iwata, Atsutoshi Kumagai

CoRR, 2022

Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation.

Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai

CoRR, 2022

Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion.

Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sharing Knowledge for Meta-learning with Feature Descriptions.

Tomoharu Iwata, Atsutoshi Kumagai

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks.

Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders.

Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Transfer Anomaly Detection for Maximizing the Partial AUC.

Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama, Yasuhiro Fujiwara

Proceedings of the International Joint Conference on Neural Networks, 2022

Fast Binary Network Hashing via Graph Clustering.

Yasuhiro Fujiwara, Masahiro Nakano, Atsutoshi Kumagai, Yasutoshi Ida, Akisato Kimura, Naonori Ueda

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Fast Algorithm for Anchor Graph Hashing.

Yasuhiro Fujiwara, Sekitoshi Kanai, Yasutoshi Ida, Atsutoshi Kumagai, Naonori Ueda

Proc. VLDB Endow., 2021

Few-shot Learning for Unsupervised Feature Selection.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

CoRR, 2021

Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection.

Tomoharu Iwata, Atsutoshi Kumagai

CoRR, 2021

Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression.

Masanori Yamada, Sekitoshi Kanai, Tomoharu Iwata, Tomokatsu Takahashi, Yuki Yamanaka, Hiroshi Takahashi, Atsutoshi Kumagai

CoRR, 2021

Meta-Learning for Relative Density-Ratio Estimation.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Semi-supervised Anomaly Detection on Attributed Graphs.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Proceedings of the International Joint Conference on Neural Networks, 2021

Fast Similarity Computation for t-SNE.

Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Naonori Ueda

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Recurrent Neural Networks for Learning Long-term Temporal Dependencies with Reanalysis of Time Scale Representation.

Kentaro Ohno, Atsutoshi Kumagai

Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

Fast and Accurate Anchor Graph-based Label Prediction.

Yasuhiro Fujiwara, Yasutoshi Ida, Atsutoshi Kumagai, Sekitoshi Kanai, Naonori Ueda

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs.

Taishi Nishiyama, Atsutoshi Kumagai, Akinori Fujino, Kazunori Kamiya

Proceedings of the Data Mining, 2021

2020

Transfer Metric Learning for Unseen Domains.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Data Sci. Eng., 2020

Few-shot Learning for Time-series Forecasting.

Tomoharu Iwata, Atsutoshi Kumagai

CoRR, 2020

Meta-learning from Tasks with Heterogeneous Attribute Spaces.

Tomoharu Iwata, Atsutoshi Kumagai

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Algorithm for the b-Matching Graph.

Yasuhiro Fujiwara, Atsutoshi Kumagai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

SILU: Strategy Involving Large-scale Unlabeled Logs for Improving Malware Detector.

Taishi Nishiyama, Atsutoshi Kumagai, Kazunori Kamiya, Kenji Takahashi

Proceedings of the IEEE Symposium on Computers and Communications, 2020

2019

Transfer Anomaly Detection by Inferring Latent Domain Representations.

Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Alchemy: Stochastic Feature Regeneration for Malicious Network Traffic Classification.

Bo Hu, Atsutoshi Kumagai, Kazunori Kamiya, Kenji Takahashi, Daniel Dalek, Ola Söderström, Kazuya Okada, Yuji Sekiya, Akihiro Nakao

Proceedings of the 43rd IEEE Annual Computer Software and Applications Conference, 2019

Fast Random Forest Algorithm via Incremental Upper Bound.

Yasuhiro Fujiwara, Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Junya Arai, Naonori Ueda

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations.

Atsutoshi Kumagai, Tomoharu Iwata

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Zero-shot Domain Adaptation without Domain Semantic Descriptors.

Atsutoshi Kumagai, Tomoharu Iwata

CoRR, 2018

Learning Dynamics of Decision Boundaries without Additional Labeled Data.

Atsutoshi Kumagai, Tomoharu Iwata

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Learning Latest Classifiers without Additional Labeled Data.

Atsutoshi Kumagai, Tomoharu Iwata

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance.

Atsutoshi Kumagai, Tomoharu Iwata

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Learning Future Classifiers without Additional Data.

Atsutoshi Kumagai, Tomoharu Iwata

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016