Multiple Social Role Embedding. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (DSAA, 2017)

Disentangled Link Prediction for Signed Social Networks via Disentangled Representation Learning. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (DSAA, 2017)

Embedding of Embedding (EOE): Joint Embedding for Coupled Heterogeneous Networks. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (WSDM, 2017)

Cross View Link Prediction by Learning Noise-resilient Representation Consensus. - Xiaokai Wei; Linchuan Xu; Bokai Cao; Philip S. Yu (WWW, 2017)

Embedding Identity and Interest for Social Networks. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (WWW (Companion Volume), 2017)

On Learning Mixed Community-specific Similarity Metrics for Cold-start Link Prediction. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (WWW (Companion Volume), 2017)

On Learning Community-specific Similarity Metrics for Cold-start Link Prediction. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (IJCNN, 2018)

Interaction Content Aware Network Embedding via Co-embedding of Nodes and Edges. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (PAKDD (2), 2018)

On Exploring Semantic Meanings of Links for Embedding Social Networks. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (WWW, 2018)

Orderly Subspace Clustering. - Jing Wang 023; Atsushi Suzuki; Linchuan Xu; Feng Tian 006; Liang Yang 002; Kenji Yamanishi (AAAI, 2019)

Attributed Subspace Clustering. - Jing Wang 023; Linchuan Xu; Feng Tian 006; Atsushi Suzuki; Changqing Zhang; Kenji Yamanishi (IJCAI, 2019)

Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression. - Yuhui Zheng; Linchuan Xu; Taichi Kiwaki; Jing Wang 023; Hiroshi Murata; Ryo Asaoka; Kenji Yamanishi (KDD, 2019)

Multi-task network embedding. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (Int. J. Data Sci. Anal., 2019)

Discovering Latent Class Labels for Multi-Label Learning. - Jun Huang 003; Linchuan Xu; Jing Wang 023; Lei Feng 006; Kenji Yamanishi (IJCAI, 2020)

Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis. - Kenji Yamanishi; Linchuan Xu; Ryo Yuki; Shintaro Fukushima; Chuan-hao Lin (CoRR, 2020)

A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification. - Linchuan Xu; Jun Huang 003; Atsushi Nitanda; Ryo Asaoka; Kenji Yamanishi (CoRR, 2020)

ICANE: interaction content-aware network embedding via co-embedding of nodes and edges. - Linchuan Xu; Xiaokai Wei; Jiannong Cao 001; Philip S. Yu (Int. J. Data Sci. Anal., 2020)

Sketch-then-Edit Generative Adversarial Network. - Wei Li 121; Linchuan Xu; Zhixuan Liang; Senzhang Wang; Jiannong Cao 001; Chao Ma 008; Xiaohui Cui (Knowl. Based Syst., 2020)

Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization. - Linchuan Xu; Jiannong Cao 001; Xiaokai Wei; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2020)

Generalization Error Bound for Hyperbolic Ordinal Embedding. - Atsushi Suzuki; Atsushi Nitanda; Jing Wang 023; Linchuan Xu; Kenji Yamanishi; Marc Cavazza (ICML, 2021)

PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma. - Linchuan Xu; Ryo Asaoka; Taichi Kiwaki; Hiroshi Murata; Yuri Fujino; Kenji Yamanishi (KDD, 2021)

Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic. - Atsushi Suzuki; Atsushi Nitanda; Jing Wang 023; Linchuan Xu; Kenji Yamanishi; Marc Cavazza (NeurIPS, 2021)

Multi-label learning with missing and completely unobserved labels. - Jun Huang 003; Linchuan Xu; Kun Qian 003; Jing Wang 023; Kenji Yamanishi (Data Min. Knowl. Discov., 2021)

JDGAN: Enhancing generator on extremely limited data via joint distribution. - Wei Li 121; Linchuan Xu; Zhixuan Liang; Senzhang Wang; Jiannong Cao 001; Thomas C. Lam; Xiaohui Cui (Neurocomputing, 2021)

MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types. - Linchuan Xu; Jing Wang 023; Lifang He 001; Jiannong Cao 001; Xiaokai Wei; Philip S. Yu; Kenji Yamanishi (IEEE Trans. Knowl. Data Eng., 2021)

RGB Color Model Aware Computational Color Naming and Its Application to Data Augmentation. - Zipei Yan; Linchuan Xu; Atsushi Suzuki; Jing Wang 023; Jiannong Cao 001; Jun Huang 003 (IEEE Big Data, 2022)

Contrastive Knowledge Graph Error Detection. - Qinggang Zhang; Junnan Dong; Keyu Duan; Xiao Huang 001; Yezi Liu; Linchuan Xu (CIKM, 2022)

VF-HM: Vision Loss Estimation Using Fundus Photograph for High Myopia. - Zipei Yan; Dong Liang; Linchuan Xu; Jiahang Li 002; Zhengji Liu; Shuai Wang 048; Jiannong Cao 001; Chea-su Kee (MICCAI (7), 2023)

Network Change Detection Based on Random Walk in Latent Space. - Chuan-hao Lin; Linchuan Xu; Kenji Yamanishi (IEEE Trans. Knowl. Data Eng., 2023)

Multi-layered semantic representation network for multi-label image classification. - Xiwen Qu; Hao Che; Jun Huang 003; Linchuan Xu; Xiao Zheng (Int. J. Mach. Learn. Cybern., 2023)

Luckiness Normalized Maximum Likelihood-based Change Detection for High-dimensional Graphical Models with Missing Data. - Zhongyi Que; Linchuan Xu; Kenji Yamanishi (IEEE Big Data, 2024)

GMMDA: Gaussian mixture modeling of graph in latent space for graph data augmentation. - Yanjin Li; Linchuan Xu; Kenji Yamanishi (Knowl. Inf. Syst., 2024)