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Takuya Maekawa
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Publications
- 2023
- [c94]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 - 2022
- [j35]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) - 2021
- [j32]Cheng Chen, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Predicting Next-use Mobile Apps Using App Semantic Representations. J. Inf. Process. 29: 597-609 (2021) - [c81]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 - 2020
- [j31]Boqi Gao, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Detecting Reinforcement Learning-Based Grey Hole Attack in Mobile Wireless Sensor Networks. IEICE Trans. Commun. 103-B(5): 504-516 (2020) - [j29]Boqi Gao, Daichi Amagata, Takuya Maekawa, Takahiro Hara:
Detecting Energy Depriving Malicious Nodes by Unsupervised Learning in Energy Harvesting Cooperative Wireless Sensor Networks. J. Inf. Process. 28: 689-698 (2020) - [c77]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 - 2019
- [c74]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 - [c71]Naoya Yoshimura, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Upsampling Inertial Sensor Data from Wearable Smart Devices using Neural Networks. ICDCS 2019: 1983-1993 - [c69]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 - [c68]Cheng Chen, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Preliminary Investigation of Predicting Next-Use Mobile Apps Using App Semantic Representations. PerCom Workshops 2019: 391-394 - [c66]Toshimitsu Kamiya, Tatsuya Nakamura, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Estimating User Contexts from Mobile Application Usage Histories. PerCom Workshops 2019: 765-770 - [c65]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 - [c64]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
- [j24]Thilina Dissanayake, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Detecting Door Events Using a Smartphone via Active Sound Sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(4): 160:1-160:26 (2018) - [c62]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 - [c60]Boqi Gao, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Environment-Adaptive Malicious Node Detection in MANETs with Ensemble Learning. ICDCS 2018: 556-566 - [c57]Naoya Yoshimura, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Preliminary Investigation of Fine-Grained Gesture Recognition With Signal Super-Resolution. PerCom Workshops 2018: 484-487 - [c56]Thilina Dissanayake, Takuya Maekawa, Daichi Amagata, Takahiro Hara:
Preliminary Investigation of Detecting Events of Indoor Objects with Smartphone Active Sound Sensing. PerCom Workshops 2018: 500-503
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