Atsutoshi Kumagai

发表

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

Taishi Nishiyama, Atsutoshi Kumagai, Kazunori Kamiya, 2020, 2020 IEEE Symposium on Computers and Communications (ISCC).

Alchemy: Stochastic Feature Regeneration for Malicious Network Traffic Classification

Bo Hu, Yuji Sekiya, Atsutoshi Kumagai, 2019, 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC).

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

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2017, AAAI.

Fast Random Forest Algorithm via Incremental Upper Bound

Yasuhiro Fujiwara, Atsutoshi Kumagai, Naonori Ueda, 2019, CIKM.

Learning Latest Classifiers without Additional Labeled Data

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2017, IJCAI.

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

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2019, AAAI.

Transfer Metric Learning for Unseen Domains

Atsutoshi Kumagai, Yasuhiro Fujiwara, Tomoharu Iwata, 2019, Data Science and Engineering.

Efficient Algorithm for the b-Matching Graph

Naonori Ueda, Yasuhiro Fujiwara, Atsutoshi Kumagai, 2020, KDD.

Few-shot Learning for Time-series Forecasting pdf

Atsutoshi Kumagai, Tomoharu Iwata, Tomoharu Iwata, 2020, ArXiv.

Zero-shot Domain Adaptation without Domain Semantic Descriptors pdf

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2018, ArXiv.

Learning Future Classifiers without Additional Data

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2016, AAAI.

Meta-learning from Tasks with Heterogeneous Attribute Spaces

Atsutoshi Kumagai, Tomoharu Iwata, Tomoharu Iwata, 2020, NeurIPS.

Transfer Anomaly Detection by Inferring Latent Domain Representations

Yasuhiro Fujiwara, Atsutoshi Kumagai, Tomoharu Iwata, 2019, NeurIPS.

Learning Dynamics of Decision Boundaries without Additional Labeled Data

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2018, KDD.

Semi-supervised Anomaly Detection on Attributed Graphs pdf

Atsutoshi Kumagai, Yasuhiro Fujiwara, Tomoharu Iwata, 2020, 2021 International Joint Conference on Neural Networks (IJCNN).

Transfer Metric Learning for Unseen Domains

Tomoharu Iwata, Yasuhiro Fujiwara, Atsutoshi Kumagai, 2020, Data Science and Engineering.

Fast and Accurate Anchor Graph-based Label Prediction

Naonori Ueda, Atsutoshi Kumagai, Yasutoshi Ida, 2021, CIKM.

Few-shot Learning for Unsupervised Feature Selection pdf

Tomoharu Iwata, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, ArXiv.

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

Tomoharu Iwata, Atsutoshi Kumagai, Tomoharu Iwata, 2021, ArXiv.

Fast Algorithm for Anchor Graph Hashing

Naonori Ueda, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, Proc. VLDB Endow..

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

Atsutoshi Kumagai, Kentaro Ohno, 2021, 2021 IEEE International Conference on Big Knowledge (ICBK).

Fast Similarity Computation for t-SNE

Naonori Ueda, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, 2021 IEEE 37th International Conference on Data Engineering (ICDE).

Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression pdf

Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, 2021, ArXiv.

Meta-Learning for Relative Density-Ratio Estimation pdf

Tomoharu Iwata, Atsutoshi Kumagai, Yasuhiro Fujiwara, 2021, NeurIPS.