Linchuan Xu

According to our database, Linchuan Xu authored at least 31 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Multi-layered semantic representation network for multi-label image classification.

Xiwen Qu, Hao Che, Jun Huang, Linchuan Xu, Xiao Zheng

Int. J. Mach. Learn. Cybern., October, 2023

Network Change Detection Based on Random Walk in Latent Space.

Chuan-hao Lin, Linchuan Xu, Kenji Yamanishi

IEEE Trans. Knowl. Data Eng., June, 2023

VF-HM: Vision Loss Estimation Using Fundus Photograph for High Myopia.

Zipei Yan, Dong Liang, Linchuan Xu, Jiahang Li, Zhengji Liu, Shuai Wang, Jiannong Cao, Chea-su Kee

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation.

Yanjin Li, Linchuan Xu, Kenji Yamanishi

Proceedings of the IEEE International Conference on Data Mining, 2023

2022

Contrastive Knowledge Graph Error Detection.

Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

RGB Color Model Aware Computational Color Naming and Its Application to Data Augmentation.

Zipei Yan, Linchuan Xu, Atsushi Suzuki, Jing Wang, Jiannong Cao, Jun Huang

Proceedings of the IEEE International Conference on Big Data, 2022

2021

MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types.

Linchuan Xu, Jing Wang, Lifang He, Jiannong Cao, Xiaokai Wei, Philip S. Yu, Kenji Yamanishi

IEEE Trans. Knowl. Data Eng., 2021

JDGAN: Enhancing generator on extremely limited data via joint distribution.

Wei Li, Linchuan Xu, Zhixuan Liang, Senzhang Wang, Jiannong Cao, Thomas C. Lam, Xiaohui Cui

Neurocomputing, 2021

Multi-label learning with missing and completely unobserved labels.

Jun Huang, Linchuan Xu, Kun Qian, Jing Wang, Kenji Yamanishi

Data Min. Knowl. Discov., 2021

Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic.

Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Generalization Error Bound for Hyperbolic Ordinal Embedding.

Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization.

Linchuan Xu, Jiannong Cao, Xiaokai Wei, Philip S. Yu

IEEE Trans. Knowl. Data Eng., 2020

Sketch-then-Edit Generative Adversarial Network.

Wei Li, Linchuan Xu, Zhixuan Liang, Senzhang Wang, Jiannong Cao, Chao Ma, Xiaohui Cui

Knowl. Based Syst., 2020

ICANE: interaction content-aware network embedding via co-embedding of nodes and edges.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Int. J. Data Sci. Anal., 2020

A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification.

Linchuan Xu, Jun Huang, Atsushi Nitanda, Ryo Asaoka, Kenji Yamanishi

CoRR, 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

Discovering Latent Class Labels for Multi-Label Learning.

Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Multi-task network embedding.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Int. J. Data Sci. Anal., 2019

Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression.

Yuhui Zheng, Linchuan Xu, Taichi Kiwaki, Jing Wang, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Attributed Subspace Clustering.

Jing Wang, Linchuan Xu, Feng Tian, Atsushi Suzuki, Changqing Zhang, Kenji Yamanishi

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Orderly Subspace Clustering.

Jing Wang, Atsushi Suzuki, Linchuan Xu, Feng Tian, Liang Yang, Kenji Yamanishi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

On Exploring Semantic Meanings of Links for Embedding Social Networks.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Interaction Content Aware Network Embedding via Co-embedding of Nodes and Edges.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

On Learning Community-specific Similarity Metrics for Cold-start Link Prediction.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017

On Learning Mixed Community-specific Similarity Metrics for Cold-start Link Prediction.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Embedding Identity and Interest for Social Networks.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Cross View Link Prediction by Learning Noise-resilient Representation Consensus.

Xiaokai Wei, Linchuan Xu, Bokai Cao, Philip S. Yu

Proceedings of the 26th International Conference on World Wide Web, 2017

Embedding of Embedding (EOE): Joint Embedding for Coupled Heterogeneous Networks.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Disentangled Link Prediction for Signed Social Networks via Disentangled Representation Learning.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Multiple Social Role Embedding.

Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017