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Journal Articles
- 2022
[j2]Yuichi Ishikawa
, Roberto Legaspi, Kei Yonekawa, Yugo Nakamura, Shigemi Ishida, Tsunenori Mine, Yutaka Arakawa:
Unsupervised Learning of Domain-Independent User Attributes. IEEE Access 10: 119649-119665 (2022)- [j1]Zhi Li, Daichi Amagata, Yihong Zhang, Takuya Maekawa, Takahiro Hara, Kei Yonekawa, Mori Kurokawa:
HML4Rec: Hierarchical meta-learning for cold-start recommendation in flash sale e-commerce. Knowl. Based Syst. 255: 109674 (2022)
Conference and Workshop Papers
- 2024
- [c18]Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa:
Mutual Information-based Preference Disentangling and Transferring for Non-overlapped Multi-target Cross-domain Recommendations. SIGIR 2024: 2124-2133 - 2023
- [c17]Rikuto Tsubouchi, Takahiro Hara, Kei Yonekawa, Shuichiro Haruta:
Unvisited Out-Of-Town POI Recommendation with Simultaneous Learning of Multiple Regions. IEEE Big Data 2023: 915-924 - [c16]Hao Niu, Duc V. Nguyen, Kei Yonekawa, Mori Kurokawa, Chihiro Ono, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
User-irrelevant Cross-domain Association Analysis for Cross-domain Recommendation with Transfer Learning. ICDAR@ICMR 2023: 37-45 - [c15]Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa:
Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations. PAKDD (3) 2023: 271-283 - [c14]Qingxin Xia, Takahiro Hara, Takuya Maekawa, Mori Kurokawa, Kei Yonekawa:
An Effective and Efficient Self-Attention Based Model for Next POI Recommendation. PerCom Workshops 2023: 478-483 - 2022
- [c13]Kei Yonekawa, Kazuhiro Saito, Mori Kurokawa:
RIDEN: Neural-based Uniform Density Histogram for Distribution Shift Detection. AIMLSystems 2022: 13:1-13:9 - [c12]Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa:
Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations. IEEE Big Data 2022: 762-769 - [c11]Mori Kurokawa, Kei Yonekawa, Shuichiro Haruta, Tatsuya Konishi, Hideki Asoh, Chihiro Ono, Masafumi Hagiwara:
Multi-view Contrastive Multiple Knowledge Graph Embedding for Knowledge Completion. ICMLA 2022: 1412-1418 - 2021
- [c10]Jun Murao, Kei Yonekawa, Mori Kurokawa, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
Concept Drift Detection with Denoising Autoencoder in Incomplete Data. MobiQuitous 2021: 541-552 - [c9]Kei Yonekawa, Shuichiro Haruta, Tatsuya Konishi, Kazuhiro Saito, Hideki Asoh, Mori Kurokawa:
A Study on Metrics for Concept Drift Detection Based on Predictions and Parameters of Ensemble Model. MobiQuitous 2021: 568-581 - 2020
- [c8]Duc Nguyen, Hao Niu, Kei Yonekawa, Mori Kurokawa, Chihiro Ono, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
On the Transferability of Deep Neural Networks for Recommender System. IAL@PKDD/ECML 2020: 22-37 - [c7]Hao Niu, Duc Nguyen, Kei Yonekawa, Mori Kurokawa, Shinya Wada, Kiyohito Yoshihara:
Multi-source Transfer Learning for Human Activity Recognition in Smart Homes. SMARTCOMP 2020: 274-277 - 2019
- [c6]Kei Yonekawa, Hao Niu, Mori Kurokawa, Arei Kobayashi, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
Advertiser-Assisted Behavioral Ad-Targeting via Denoised Distribution Induction. IEEE BigData 2019: 5611-5619 - [c5]Kei Yonekawa, Hao Niu, Mori Kurokawa, Arei Kobayashi, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting. PAKDD (Workshops) 2019: 274-285 - [c4]Yuan Lyu, Daichi Amagata, Takuya Maekawa, Takahiro Hara, Hao Niu, Kei Yonekawa, Mori Kurokawa:
Behavior Matching between Different Domains based on Canonical Correlation Analysis. WWW (Companion Volume) 2019: 361-366 - [c3]Hanxin Wang, Daichi Amagata, Takuya Maekawa, Takahiro Hara, Hao Niu, Kei Yonekawa, Mori Kurokawa:
Preliminary Investigation of Alleviating User Cold-Start Problem in E-commerce with Deep Cross-Domain Recommender System. WWW (Companion Volume) 2019: 398-403 - 2018
- [c2]Mori Kurokawa, Hao Niu, Kei Yonekawa, Arei Kobayashi, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
Virtual Touch-Point: Trans-Domain Behavioral Targeting via Transfer Learning. IEEE BigData 2018: 4762-4767 - [c1]Yujin Tang, Kei Yonekawa, Mori Kurokawa, Shinya Wada, Kiyohito Yoshihara:
Binary Classification of Sequences Possessing Unilateral Common Factor with AMS and APR. PAKDD (3) 2018: 322-334
Informal and Other Publications
- 2022
- [i1]Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa:
Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations. CoRR abs/2211.03390 (2022)
Coauthor Index
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