Publications
[2024]
Future-Proofing Class-Incremental Learning
Quentin Jodelet, Xin Liu, Phua Yin Jun, and Tsuyoshi Murata
Machine Vision and Applications, to appear
How Powerful is Graph Filtering for Recommendation
Shaowen Peng, Xin Liu, Kazunari Sugiyama, and Tsunenori Mine
Proceedings of KDD’24, pp.2388-2399. https://doi.org/10.1145/3637528.3671789
S3PaR: Section-Based Sequential Scientific Paper Recommendation for Paper Writing Assistance
Natasha Christabelle Santosa, Xin Liu, Hyoil Han, and Jun Miyazaki
Knowledge-Based Systems, vol.303, 112437, 2024. https://doi.org/10.1016/j.knosys.2024.112437
Inexact Graph Representation Learning
Yijun Duan, Xin Liu, Adam Jatowt, Hai-Tao Yu, Steven Lynden, and Akiyoshi Matono
Proceedings of IJCNN’24. https://doi.org/10.1109/IJCNN60899.2024.10649995
DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise
Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, and Tsuyoshi Murata
Proceedings of PAKDD’24, pp.376-389. https://doi.org/10.1007/978-981-97-2253-2_30
A Decoupling and Aggregating Framework for Joint Extraction of Entities and Relations
Yao Wang, Xin Liu, Weikun Kong, Hai-Tao Yu, Teeradaj Racharak, Kyoung-Sook Kim, and Minh Le Nguyen
IEEE Access, vol.12, pp.103313–103328, 2024. https://doi.org/10.1109/ACCESS.2024.3420877
Predicting Popularity Trend in Social Media Networks with Multi-layer Temporal Graph Neural Networks
Ruidong Jin, Xin Liu, and Tsuyoshi Murata
Complex & Intelligent Systems, vol.10, pp.4713–4729, 2024. https://doi.org/10.1007/s40747-024-01402-6
[2023]
Predicting Potential Real-Time Donations in YouTube Live Streaming Services via Continuous-Time Dynamic Graphs
Ruidong Jin, Xin Liu, and Tsuyoshi Murata
Machine Learning, vol.113, pp.2093–2127, 2023. https://doi.org/10.1007/s10994-023-06449-z
MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning
Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim, and Masashi Matsuoka
Proceedings of ACM MM’23, pp.2535-2543. https://doi.org/10.1145/3581783.3613762
What Wikipedia Misses about Yuriko Nakamura? Predicting Missing Biography Content by Learning Latent Life Patterns
Yijun Duan, Xin Liu, Adam Jatowt, Chenyi Zhuang, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
Proceedings of ECAI’23, pp.583-589. https://doi.org/10.3233/FAIA230319
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation
Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim, Takayuki Shinohara, Qiong Chang, and Masashi Matsuoka
Neurocomputing, vol.559, 126780, 2023. https://doi.org/10.1016/j.neucom.2023.126780
Class-Incremental Learning Using Diffusion Model for Distillation and Replay
Quentin Jodelet, Xin Liu, Phua Yin Jun, and Tsuyoshi Murata
Proceedings of ICCV’23 Workshops, pp.3417-3425. https://doi.org/10.1109/ICCVW60793.2023.00367 [Best Paper Award]
Commonsense Temporal Action Knowledge (CoTAK) Dataset
Steven Lynden, Hailemariam Mehari, Kyoung-Sook Kim, Adam Jatowt, Akiyoshi Matono, Hai-Tao Yu, Xin Liu, and Yijun Duan
Proceedings of CIKM’23, pp.5361–5365. https://doi.org/10.1145/3583780.3615114 [Short Paper]
https://dl.acm.org/doi/10.1145/3583780.3615114
Feature Selection: Key to Enhance Node Classification with Graph Neural Networks
Sunil Kumar Maurya, Xin Liu, and Tsuyoshi Murata
CAAI Transactions on Intelligence Technology, vol.8, pp.14-28, 2023. https://doi.org/10.1049/cit2.12166
StereoVAE: A Lightweight Stereo-Matching System Using Embedded GPUs
Qiong Chang, Xiang Li, Xiang Li, Xin Xu, Xin Liu, Yun Li, and Jun Miyazaki
Proceedings of ICRA’23, pp.1982-1988. https://doi.org/10.1109/ICRA48891.2023.10160441
DS-Net: A Dedicated Approach for Collapsed Building Detection from Post-Event Airborne Point Clouds
Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim, Takayuki Shinohara, Qiong Chang, and Masashi Matsuoka
International Journal of Applied Earth Observation and Geoinformation, vol.116, 103150, 2023. https://doi.org/10.1016/j.jag.2022.103150
QSD-LSTM: Vessel Trajectory Prediction Us-ing Long Short-Term Memory with Quaternion Ship Domain
Ryan Wen Liu, Kunlin Hu, Maohan Liang, Yan Li, Xin Liu, and Dong Yang
Applied Ocean Research, vol.136, 103592, 2023. https://doi.org/10.1016/j.apor.2023.103592
Optimizing Local Feature Representations of 3D Point Clouds with Anisotropic Edge Modeling
Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim, Takayuki Shinohara, Qiong Chang, and Masashi Matsuoka
Proceedings of MMM’23, pp.269-281. https://doi.org/10.1007/978-3-031-27077-2_21
WeExt: A Framework of Extending Deterministic Knowledge Graph Embedding Models for Embedding Weighted Knowledge Graphs
Weikun Kong, Xin Liu, Teeradaj Racharak, Guanqun Sun, Jianan Chenand, Qiang Ma, and Minh Le Nguyen
IEEE Access, vol.11, pp.48901-48911, 2023. https://doi.org/10.1109/ACCESS.2023.3276319
[2022]
Heterogeneous Graph Embedding with Single-Level Aggregation and Infomax Encoding
Nuttapong Chairatanakul, Xin Liu, Nguyen Thai Hoang, and Tsuyoshi Murata
Machine Learning, vol.112, pp.4227–4256, 2022. https://doi.org/10.1007/s10994-022-06160-5
Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs
Yijun Duan, Xin Liu, Adam Jatowt, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
Proceedings of ECML-PKDD’2022, pp.20-36. https://doi.org/10.1007/978-3-031-26390-3_2
Balanced Softmax Cross-Entropy for Incremental Learning with and without Memory
Quentin Jodelet, Xin Liu, and Tsuyoshi Murata
Computer Vision and Image Understanding, vol.225, 103582, 2022. https://doi.org/10.1016/j.cviu.2022.103582
Leaping Through Time with Gradient-Based Adaptation for Recommendation
Nuttapong Chairatanakul, Nguyen Thai Hoang, Xin Liu, and Tsuyoshi Murata
Proceedings of AAAI’22, pp.6141-6149. https://doi.org/10.1609/aaai.v36i6.20562
Dual Cost-Sensitive Graph Convolutional Network Learning for Imbalanced Graph Node Classification
Yijun Duan, Xin Liu, Adam Jatowt, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
Proceedings of IJCNN’22. https://doi.org/10.1109/IJCNN55064.2022.9892598
Not All Neighbors are Friendly: Learning to Choose Hop Features to Improve Node Classification
Sunil Kumar Maurya, Xin Liu, and Tsuyoshi Murata
Proceedings of CIKM’22, pp.4334-4338. https://doi.org/10.1145/3511808.3557543 [Short Paper]
TransHExt: a Weighted Extension for TransH on Weighted Knowledge Graph Embedding
Weikun Kong, Xin Liu, Teeradaj Racharak, and Minh Le Nguyen
Proceedings of ISWC’22 [Poster]
Predicting Potential Real-time Donations in YouTube Live Streaming Services via Continuous-Time Dynamic Graph
Ruidong Jin, Xin Liu, and Tsuyoshi Murata
Proceedings of DS’22, pp.59-73. https://doi.org/10.1007/978-3-031-18840-4_5
Strengthening Robustness under Adversarial Attacks Using Brain Visual Codes
Zarina Rakhimberdina, Xin Liu, and Tsuyoshi Murata
IEEE Access, vol.10, pp.96149-96158, 2022. https://doi.org/10.1109/ACCESS.2022.3204995
Multiview Actionable Knowledge Graph Generation From Wikipedia Biographies
Yijun Duan, Xin Liu, Adam Jatowt, Chenyi Zhuang, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
IEEE Access, vol.10, pp.73879-73892, 2022. https://doi.org/10.1109/ACCESS.2022.3189769
SORAG: Synthetic Data Over-sampling Strategy on Multi-Label Graphs
Yijun Duan, Xin Liu, Adam Jatowt, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
Remote Sensing, vol.14, 4479, 2022. https://doi.org/10.3390/rs14184479
Long-tailed Graph Representation Learning via Dual Cost-sensitive Graph Convolutional Network
Yijun Duan, Xin Liu, Adam Jatowt, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, and Akiyoshi Matono
Remote Sensing, vol.14, 3295, 2022. https://doi.org/10.3390/rs14143295
Efficient Stereo Matching on Embedded GPUs with Zero-Means Cross Correlation
Qiong Chang, Aolong Zha, Weimin Wang, Xin Liu, Masaki Onishi, Lei Lei, Meng Joo Er, Tsutomu Maruyama
Journal of Systems Architecture, vol.123, 102366, 2022. https://doi.org/10.1016/j.sysarc.2021.102366
Simplifying Approach to Node Classification in Graph Neural Networks
Sunil Kumar Maurya, Xin Liu, and Tsuyoshi Murata
Journal of Computational Science, vol.62, 101695, 2022. https://doi.org/10.1016/j.jocs.2022.101695
Enhancing Citation Recommendation Using Citation Network Embedding
Chanathip Pornprasit, Xin Liu, Pattararat Kiattipadungkul, Natthawut Kertkeidkachorn, Kyoung-Sook Kim, Thanapon Noraset, Saeed-Ul Hassan, and Suppawong Tuarob
Scientometrics, vol.127, pp.233-264, 2022. https://doi.org/10.1007/s11192-021-04196-3
[2021]
Graph Convolutional Networks for Graphs Containing Missing Features
Hibiki Taguchi, Xin Liu, and Tsuyoshi Murata
Future Generation Computer Systems, vol.117, pp.155-168, 2021. https://doi.org/10.1016/j.future.2020.11.016
Graph Neural Networks for Fast Node Ranking Approximation
Sunil Kumar Maurya, Xin Liu, and Tsuyoshi Murata
ACM Transactions on Knowledge Discovery from Data, vol.15, no.5, article 78, 2021. https://doi.org/10.1145/3446217
PGRA: Projected Graph Relation-Feature Attention Network for Heterogeneous Information Network Embedding
Nuttapong Chairatanakul, Xin Liu, and Tsuyoshi Murata
Information Sciences, vol.570, pp.769-794, 2021. https://doi.org/10.1016/j.ins.2021.04.070
Natural Image Reconstruction from fMRI Using Deep Learning: A Survey
Zarina Rakhimberdina, Quentin Jodelet, Xin Liu, and Tsuyoshi Murata
Frontiers in Neuroscience, vol.15, 795488, 2021. https://doi.org/10.3389/fnins.2021.795488
Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-Graph Convolution Network
Zhaonan Wang, Tianqi Xia, Renhe Jiang, Xin Liu, Kyoung-Sook Kim, Xuan Song, and Ryosuke Shibasaki
Proceedings of ICDE’21, pp.1751-1762. https://doi.org/10.1109/ICDE51399.2021.00154
Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction
Zhaonan Wang, Renhe Jiang, Zekun Cai, Zipei Fan, Xin Liu, Kyoung-Sook Kim, Xuan Song, and Ryosuke Shibasaki
Proceedings of CIKM’21, pp.2060-2069. https://doi.org/10.1145/3459637.3482482
Enhancing Local Feature Learning for 3D Point Cloud Processing Using Unary-Pairwise Attention
Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim, Takayuki Shinohara, Qiong Chang, and Masashi Matsuoka
Proceedings of BMVC’21, article 678
Cross-lingual Transfer for Text Classification with Dictionary-Based Heterogeneous Graph
Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee, Xin Liu, and Tsuyoshi Murata
Findings of EMNLP’21, pp.1504-1517. https://doi.org/10.18653/v1/2021.findings-emnlp.130
Balanced Softmax Cross-Entropy for Incremental Learning
Quentin Jodelet, Xin Liu, and Tsuyoshi Murata
Proceedings of ICANN’21, pp.385-396. https://doi.org/10.1007/978-3-030-86340-1_31
Diachronic Linguistic Periodization of Temporal Document Collections for Discovering Evolutionary Word Semantics
Yijun Duan, Adam Jatowt, Masatoshi Yoshikawa, Xin Liu, and Akiyoshi Matono
Proceedings of ICADL’21, pp.3-17. https://doi.org/10.1007/978-3-030-91669-5_1
Predicting Emergency Medical Service Demand with Bipartite Graph Convolutional Networks
Ruidong Jin, Tianqi Xia, Xin Liu, Tsuyoshi Murata, and Kyoung-Sook Kim
IEEE Access, vol.9, pp.9903-9915, 2021. https://doi.org/10.1109/ACCESS.2021.3050607
An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation
Maohan Liang, Wen Liu, Shichen Li, Zhe Xiao, Xin Liu, and Feng Lu
Ocean Engineering, vol.225, 108803, 2021. https://doi.org/10.1016/j.oceaneng.2021.108803
Structure-Guided Attributed Network Embedding with ‘‘Centroid’’ Enhancement
Zihan Liao, Wenxin Liang, Beilei Cui, and Xin Liu
Computing, vol.103, pp.1599-1620, 2021. https://doi.org/10.1007/s00607-021-00916-y
[2020]
Towards Temporal Knowledge Graph Embeddings with Arbitrary Time Precision
Julien Leblay, Melisachew Wudage Chekol, and Xin Liu
Proceedings of CIKM’20, pp.685-694. https://doi.org/10.1145/3340531.3412028
ConvCN: A CNN-Based Citation Network Embedding Algorithm Towards Citation Recommendation
Chanathip Pornprasit, Xin Liu, Natthawut Kertkeidkachorn, Kyoung-Sook Kim, Thanapon Noraset, and Suppawong Tuarob
Proceedings of JCDL’20, pp.433-436. https://doi.org/10.1145/3383583.3398609 [Short Paper]
BiMLPA: Community Detection in Bipartite Networks by Multi-Label Propagation
Hibiki Taguchi, Tsuyoshi Murata, and Xin Liu
Proceedings of NetSci-X’20, pp.17-31. https://doi.org/10.1007/978-3-030-38965-9_2
Population Graph-Based Multi-Model Ensemble Method for Diagnosing
Zarina Rakhimberdina, Xin Liu, and Tsuyoshi Murata
Sensors, vol.20, 6001, 2020. https://doi.org/10.3390/s20216001
Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization
JunJin Choong, Xin Liu, and Tsuyoshi Murata
Entropy, vol.22, no.2, 197, 2020. https://doi.org/10.3390/e22020197
Z$^2$-ZNCC: ZigZag Scanning based Zero-means Normalized Cross Correlation for Fast and Accurate Stereo Matching on Embedded GPU
Qiong Chang, Aolong Zha, Weimin Wang, Xin Liu, Masaki Onishi, and Tsutomu Maruyama
Proceedings of ICCD’20, pp.597-600. https://doi.org/10.1109/ICCD50377.2020.00104 [Short Paper]
CoolPath: An Application for Recommending Pedestrian Routes with Reduced Heatstroke Risk
Tianqi Xia, Adam Jatowt, Zhaonan Wang, Ruochen Si, Haoran Zhang, Xin Liu, Ryosuke Shibasaki, Xuan Song, and Kyoung-sook Kim
Proceedings of W2GIS’20, pp.14-23. https://doi.org/10.1007/978-3-030-60952-8_2
[2019]
A General View for Network Embedding as Matrix Factorization
Xin Liu, Tsuyoshi Murata, Kyoung-Sook Kim, Chatchawan Kotarasu, and Chenyi Zhuang
Proceedings of WSDM’19, pp.375-383. https://doi.org/10.1145/3289600.3291029
Fast Approximations of Betweenness Centrality with Graph Neural Networks
Sunil Kumar Maurya, Xin Liu, and Tsuyoshi Murata
Proceedings of CIKM’19, pp.2149-2152. https://doi.org/10.1145/3357384.3358080 [Short Paper]
Recurrent Translation-Based Network for Top-N Sparse Sequential Recommendation
Nuttapong Chairatanakul, Tsuyoshi Murata, Xin Liu
IEEE Access, vol.7, pp.131567-131576, 2019. https://doi.org/10.1109/ACCESS.2019.2941083
How Much Topological Structure is Preserved by Graph Embeddings?
Xin Liu, Chenyi Zhuang, Tsuyoshi Murata, Kyoung-Sook Kim, and Natthawut Kertkeidkachorn
Computer Science and Information Systems, vol.16, no.2, pp.597-614, 2019. https://doi.org/10.2298/CSIS181001011L
Knowledge Representation of G-Protein-Coupled Receptor Signal Transduction Pathways
Natthawut Kertkeidkachorn, Lihua Zhao, Xin Liu, and Ryutaro Ichise
Proceedings of ICSC’19, pp.324-329. https://doi.org/10.1109/ICOSC.2019.8665519
GTransE: Generalizing Translation-Based Model on Uncertain Knowledge Graph Embedding
Natthawut Kertkeidkachorn, Xin Liu, and Ryutaro Ichise
Proceedings of JSAI’19, pp.170-178. https://doi.org/10.1007/978-3-030-39878-1_16
Optimizing Variational Graph Autoencoder for Community Detection
JunJin Choong, Xin Liu, and Tsuyoshi Murata
Proceedings of IEEE BigData’19 Workshops, pp.5353-5358. https://doi.org/10.1109/BigData47090.2019.9006123
[2018]
Learning Community Structure with Variational Autoencoder
JunJin Choong, Xin Liu, and Tsuyoshi Murata
Proceedings of ICDM’18, pp.69-78. https://doi.org/10.1109/ICDM.2018.00022
Network Embedding Based on a Quasi-Local Similarity Measure
Xin Liu, Natthawut Kertkeidkachorn, Tsuyoshi Murata, Kyoung-Sook Kim, Julien Leblay and Steven Lynden
Proceedings of PRICAI’18, pp.429-440. https://doi.org/10.1007/978-3-319-97304-3_33
Measuring Graph Reconstruction Precisions: How Well Do Embeddings Preserve the Graph Proximity Structure?
Xin Liu, Tsuyoshi Murata, and Kyoung-Sook Kim
Proceedings of WIMS’18, article 25. https://doi.org/10.1145/3227609.3227673
Variational Approach for Learning Community Structures
JunJin Choong, Xin Liu, and Tsuyoshi Murata
Complexity, vol.2018, article 4867304, 2018. https://doi.org/10.1155/2018/4867304
[Up to 2017]
Food Sales Prediction with Meteorological Data: A Case Study of a Japanese Chain Supermarket
Xin Liu and Ryutaro Ichise
Proceedings of DMBD’17, pp.93-104. https://doi.org/10.1007/978-3-319-61845-6_10
Towards an Aggregator That Exploits Big Data to Bid on Frequency Containment Reserve Market
Christian Giovanelli, Xin Liu, Seppo Sierla, Valeriy Vyatkin, and Ryutaro Ichise
Proceedings of IECON’17, pp.7514-7519. https://doi.org/10.1109/IECON.2017.8217316
Community Detection in Multi-Partite Multi-Relational Networks Based on Information Compression
Xin Liu, Weichu Liu, Tsuyoshi Murata, and Ken Wakita
New Generation Computing, vol.34, pp.153-176, 2016. https://doi.org/10.1007/s00354-016-0206-1
Detecting Network Communities Beyond Assortativity-Related Attributes
Xin Liu, Tsuyoshi Murata, and Ken Wakita
Physical Review E, vol.90, 012806, 2014. https://doi.org/10.1103/PhysRevE.90.012806
A Framework for Community Detection in Heterogeneous Multi-Relational Networks
Xin Liu, Weichu Liu, Tsuyoshi Murata, and Ken Wakita
Advances in Complex Systems, vol.17, no.6, 1450018, 2014. https://doi.org/10.1142/S0219525914500180
A Unified Modularity by Encoding the Similarity Attraction Feature into the Null Model
Xin Liu, Tsuyoshi Murata, and Ken Wakita
Proceedings of ASONAM’14, pp.521-528. https://doi.org/10.1109/ASONAM.2014.6921636
Extracting the Multilevel Communities Based on Network Structural and Nonstructural Information
Xin Liu, Tsuyoshi Murata, and Ken Wakita
Proceedings of WWW’13, pp.191-192. https://doi.org/10.1145/2487788.2487884 [Poster]
Community Detection Algorithm Based on Centrality and Node Distance in Scale-Free Networks
Sorn Jarukasemratana, Tsuyoshi Murata, and Xin Liu
Proceedings of HT’13, pp.258-262. https://doi.org/10.1145/2481492.2481527
Detecting Communities in K-Partite K-Uniform (Hyper)Networks
Xin Liu and Tsuyoshi Murata
Journal of Computer Science and Technology, vol.26, no.5, pp.778-791, 2011. https://doi.org/10.1007/s11390-011-0177-0
Extracting the Mesoscopic Structure from Heterogeneous Systems
Xin Liu and Tsuyoshi Murata
Proceedings of HT’11, pp.211-220. https://doi.org/10.1145/1995966.1995995
Advanced Modularity-Specialized Label Propagation Algorithm for Detecting Communities in Networks
Xin Liu and Tsuyoshi Murata
Physica A, vol.389, no.7, pp.1493-1500, 2010. https://doi.org/10.1016/j.physa.2009.12.019
An Efficient Algorithm for Optimizing Bipartite Modularity in Bipartite Networks
Xin Liu and Tsuyoshi Murata
Journal of Advanced Computational Intelligence and Intelligent Informatics, vol.14, no.4, pp.408-415, 2010. https://doi.org/10.20965/jaciii.2010.p0408
Evaluating Community Structure in Bipartite Networks
Xin Liu and Tsuyoshi Murata
Proceedings of SocialCom’10, pp.576-581. https://doi.org/10.1109/SocialCom.2010.91
Community Detection in Large-Scale Bipartite Networks
Xin Liu and Tsuyoshi Murata
Proceedings of WI’09, vol.1, pp.50-57. https://doi.org/10.1109/WI-IAT.2009.15
How Does Label Propagation Algorithm Work in Bipartite Networks?
Xin Liu and Tsuyoshi Murata
Proceedings of WI’09 Workshops, pp.5-8. https://doi.org/10.1109/WI-IAT.2009.217
Effective Algorithm for Detecting Community Structure in Complex Networks Based on GA and Clustering
Xin Liu, Deyi Li, Shuliang Wang, and Zhiwei Tao
Proceedings of ICCS’07, pp.657-664. https://doi.org/10.1007/978-3-540-72586-2_95