Linchuan Xu

37 papers A* 10A 2B 6Journal 15Unranked 4
YearRankTypeTitle / Venue / Authors
2024 J jnl
GMMDA: Gaussian mixture modeling of graph in latent space for graph data augmentation.
Knowl. Inf. Syst.
Yanjin Li, Linchuan Xu, Kenji Yamanishi
2024 B conf
Luckiness Normalized Maximum Likelihood-based Change Detection for High-dimensional Graphical Models with Missing Data.
IEEE Big Data
Zhongyi Que, Linchuan Xu, Kenji Yamanishi
2023 A* conf
GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation.
ICDM
Yanjin Li, Linchuan Xu, Kenji Yamanishi
2023 J jnl
Multi-layered semantic representation network for multi-label image classification.
Int. J. Mach. Learn. Cybern.
Xiwen Qu, Hao Che, Jun Huang, Linchuan Xu, Xiao Zheng
2023 J jnl
Network Change Detection Based on Random Walk in Latent Space.
IEEE Trans. Knowl. Data Eng.
Chuan-hao Lin, Linchuan Xu, Kenji Yamanishi
2023 — conf
VF-HM: Vision Loss Estimation Using Fundus Photograph for High Myopia.
MICCAI (7)
Zipei Yan, Dong Liang, Linchuan Xu, Jiahang Li, Zhengji Liu, Shuai Wang, Jiannong Cao, Chea-su Kee
2022 A conf
Contrastive Knowledge Graph Error Detection.
CIKM
Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu
2022 J jnl
Contrastive Knowledge Graph Error Detection.
CoRR
Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu
2022 B conf
RGB Color Model Aware Computational Color Naming and Its Application to Data Augmentation.
IEEE Big Data
Zipei Yan, Linchuan Xu, Atsushi Suzuki, Jing Wang, Jiannong Cao, Jun Huang
2021 A* conf
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic.
NeurIPS
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza
2021 A* conf
Generalization Error Bound for Hyperbolic Ordinal Embedding.
ICML
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza
2021 J jnl
Generalization Error Bound for Hyperbolic Ordinal Embedding.
CoRR
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Marc Cavazza, Kenji Yamanishi
2021 J jnl
JDGAN: Enhancing generator on extremely limited data via joint distribution.
Neurocomputing
Wei Li, Linchuan Xu, Zhixuan Liang, Senzhang Wang, Jiannong Cao, Thomas C. Lam, Xiaohui Cui
2021 J jnl
MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types.
IEEE Trans. Knowl. Data Eng.
Linchuan Xu, Jing Wang, Lifang He, Jiannong Cao, Xiaokai Wei, Philip S. Yu, Kenji Yamanishi
2021 J jnl
Multi-label learning with missing and completely unobserved labels.
Data Min. Knowl. Discov.
Jun Huang, Linchuan Xu, Kun Qian, Jing Wang, Kenji Yamanishi
2021 J jnl
Multi-layered Semantic Representation Network for Multi-label Image Classification.
CoRR
Xiwen Qu, Hao Che, Jun Huang, Linchuan Xu, Xiao Zheng
2021 A* conf
PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma.
KDD
Linchuan Xu, Ryo Asaoka, Taichi Kiwaki, Hiroshi Murata, Yuri Fujino, Kenji Yamanishi
2020 J jnl
A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification.
CoRR
Linchuan Xu, Jun Huang, Atsushi Nitanda, Ryo Asaoka, Kenji Yamanishi
2020 J jnl
Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis.
CoRR
Kenji Yamanishi, Linchuan Xu, Ryo Yuki, Shintaro Fukushima, Chuan-hao Lin
2020 A* conf
Discovering Latent Class Labels for Multi-Label Learning.
IJCAI
Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi
2020 J jnl
ICANE: interaction content-aware network embedding via co-embedding of nodes and edges.
Int. J. Data Sci. Anal.
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2020 J jnl
Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization.
IEEE Trans. Knowl. Data Eng.
Linchuan Xu, Jiannong Cao, Xiaokai Wei, Philip S. Yu
2020 J jnl
Sketch-then-Edit Generative Adversarial Network.
Knowl. Based Syst.
Wei Li, Linchuan Xu, Zhixuan Liang, Senzhang Wang, Jiannong Cao, Chao Ma, Xiaohui Cui
2019 A* conf
Attributed Subspace Clustering.
IJCAI
Jing Wang, Linchuan Xu, Feng Tian, Atsushi Suzuki, Changqing Zhang, Kenji Yamanishi
2019 A* conf
Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression.
KDD
Yuhui Zheng, Linchuan Xu, Taichi Kiwaki, Jing Wang, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi
2019 J jnl
Multi-task network embedding.
Int. J. Data Sci. Anal.
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2019 A* conf
Orderly Subspace Clustering.
AAAI
Jing Wang, Atsushi Suzuki, Linchuan Xu, Feng Tian, Liang Yang, Kenji Yamanishi
2018 — conf
Interaction Content Aware Network Embedding via Co-embedding of Nodes and Edges.
PAKDD (2)
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2018 A* conf
On Exploring Semantic Meanings of Links for Embedding Social Networks.
WWW
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2018 B conf
On Learning Community-specific Similarity Metrics for Cold-start Link Prediction.
IJCNN
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 A* conf
Cross View Link Prediction by Learning Noise-resilient Representation Consensus.
WWW
Xiaokai Wei, Linchuan Xu, Bokai Cao, Philip S. Yu
2017 B conf
Disentangled Link Prediction for Signed Social Networks via Disentangled Representation Learning.
DSAA
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 — conf
Embedding Identity and Interest for Social Networks.
WWW (Companion Volume)
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 A conf
Embedding of Embedding (EOE): Joint Embedding for Coupled Heterogeneous Networks.
WSDM
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 B conf
Multi-task Network Embedding.
DSAA
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 B conf
Multiple Social Role Embedding.
DSAA
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu
2017 — conf
On Learning Mixed Community-specific Similarity Metrics for Cold-start Link Prediction.
WWW (Companion Volume)
Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu