Lin Wang

According to our database, Lin Wang authored at least 15 papers between 2019 and 2025.

Collaborative distances:

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

2025

HORAE: Temporal Multi-Interest Pre-training for Sequential Recommendation.

Shirui Hu, Weichang Wu, Zuoli Tang, Zhaoxin Huan, Lin Wang, Xiaolu Zhang, Jun Zhou, Lixin Zou, Chenliang Li

ACM Trans. Inf. Syst., July, 2025

2024

AntBatchInfer: Elastic Batch Inference in the Kubernetes Cluster.

Siyuan Li, Youshao Xiao, Fanzhuang Meng, Lin Ju, Lei Liang, Lin Wang, Jun Zhou

CoRR, 2024

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes.

Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, Zhaoxin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou

CoRR, 2024

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes.

Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, Zhaoxin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing.

Jin Zhao, Yu Zhang, Ligang He, Qikun Li, Xiang Zhang, Xinyu Jiang, Hui Yu, Xiaofei Liao, Hai Jin, Lin Gu, Haikun Liu, Bingsheng He, Ji Zhang, Xianzheng Song, Lin Wang, Jun Zhou

ACM Trans. Archit. Code Optim., September, 2023

SQLFlow: An Extensible Toolkit Integrating DB and AI.

Jun Zhou, Ke Zhang, Lin Wang, Hua Wu, Yi Wang, Chaochao Chen

J. Mach. Learn. Res., 2023

ElasticDL: A Kubernetes-native Deep Learning Framework with Fault-tolerance and Elastic Scheduling.

Jun Zhou, Ke Zhang, Feng Zhu, Qitao Shi, Wenjing Fang, Lin Wang, Yi Wang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network.

Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Towards Multi-Interest Pre-training with Sparse Capsule Network.

Zuoli Tang, Lin Wang, Lixin Zou, Xiaolu Zhang, Jun Zhou, Chenliang Li

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs.

Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data.

Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu

Proceedings of the Database Systems for Advanced Applications, 2023

G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems.

Youshao Xiao, Shangchun Zhao, Zhenglei Zhou, Zhaoxin Huan, Lin Ju, Xiaolu Zhang, Lin Wang, Jun Zhou

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2020

AGL: A Scalable System for Industrial-purpose Graph Machine Learning.

Dalong Zhang, Xin Huang, Ziqi Liu, Jun Zhou, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Lin Wang, Zhiqiang Zhang, Yuan Qi

Proc. VLDB Endow., 2020

AGL: a Scalable System for Industrial-purpose Graph Machine Learning.

Dalong Zhang, Xin Huang, Ziqi Liu, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Zhiqiang Zhang, Lin Wang, Jun Zhou, Shuang Yang, Yuan Qi

CoRR, 2020

2019

DSSLP: A Distributed Framework for Semi-supervised Link Prediction.

Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019