Publications

You can also find my articles in my Google Scholar.
(^* indicates equal contribution. )

Conference Papers

Achieving Fairness Generalizability for Learning-based Congestion Control with Jury
Han Tian, Xudong Liao, Decang Sun, Chaoliang Zeng, Yilun Jin, Junxue Zhang, Xinchen Wan, Zilong Wang, Yong Wang, Kai Chen.
To appear in European Conference on Conputer Systems (EuroSys), 2025.

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models [pdf][data][slides]
Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Sridatt Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin.
To appear in the Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2024.
Efficient Decentralized Federated Singular Vector Decomposition [pdf]
Di Chai, Junxue Zhang, Liu Yang, Yilun Jin, Leye Wang, Kai Chen, Qiang Yang.
In the 2024 USENIX Annual Technical Conference (ATC), 2024.
Understanding Communication Characteristics of Distributed Training [pdf]
Wenxue Li, Xiangzhou Liu, Yuxuan Li, Yilun Jin, Han Tian, Zhizhen Zhong, Guyue Liu, Ying Zhang, Kai Chen.
In the 8th Asia-Pacific Workshop on Networking (APNet), 2024.
Accelerating Privacy-Preserving Machine Learning With GeniBatch [pdf]
Xinyang Huang, Junxue Zhang, Xiaodian Cheng, Hong Zhang, Yilun Jin, Shuihai Hu, Han Tian, Kai Chen.
In European Conference on Computer Systems (EuroSys), 2024.

Transferable Graph Structure Learning for Graph-based Traffic Forecasting across Cities [pdf]
Yilun Jin, Kai Chen, Qiang Yang.
In the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Scalable and Efficient Full-Graph GNN Training for Large Graphs [pdf]
Xinchen Wan, Kaiqiang Xu, Xudong Liao, Yilun Jin, Kai Chen, Xin Jin.
In the ACM Conference on Management of Data (SIGMOD), 2023.
MDP: Model Decomposition and Parallelization of Vision Transformer for Distributed Edge Inference [pdf]
Weiyan Wang, Yiming Zhang, Yilun Jin, Han Tian, Li Chen
To appear in IEEE International Conference on Mobility, Sensing, and Networking (MSN), 2023.

Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting [pdf][code][slides]
Yilun Jin, Kai Chen, Qiang Yang.
In the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels [pdf][code][talk]
Qingqing Long^*, Yilun Jin^*, Yi Wu^*, Guojie Song.
In The Web Conference (TheWebConf, a.k.a. WWW), 2021.
GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks [pdf][code]
Yi Li, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi, Yiming Wang.
In the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021

GraLSP: Graph Neural Networks with Local Structural Patterns [pdf][code]
Yilun Jin, Guojie Song, Chuan Shi.
In The 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
Graph Structural-topic Neural Network [pdf][code][slides][talk]
Qingqing Long^*, Yilun Jin^*, Guojie Song, Yi Li, Wei Lin.
In The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
EPNE: Evolutionary Pattern Preserving Network Embedding [pdf]
Junshan Wang^*, Yilun Jin^*, Guojie Song, Xiaojun Ma.
In The 24th European Conference on Artificial Intelligence (ECAI), 2020
Domain Adaptive Classification on Heterogeneous Information Networks [pdf][code]
Shuwen Yang, Guojie Song, Yilun Jin, Lun Du.
In The 29th International Joint Conference on Artificial Intelligence (IJCAI-PRICAI), 2020.
Active Domain Transfer on Network Embedding [pdf]
Lichen Jin, Yizhou Zhang, Guojie Song, Yilun Jin,
In The Web Conference (TheWebConf, a.k.a. WWW), 2020.

Hierarchical Community Structure Preserving Network Embedding: A Subspace Approach [pdf][code]
Qingqing Long, Yiming Wang, Lun Du, Guojie Song, Yilun Jin, Wei Lin.
In The 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019. Best Research Paper Runner-up Award.
DANE: Domain Adaptive Network Embedding [pdf]
Yizhou Zhang, Guojie Song, Lun Du, Shuwen Yang, Yilun Jin.
In The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.

Federated Learning without Full Labels: A Survey [pdf]
Yilun Jin, Yang Liu, Kai Chen, Qiang Yang.
In IEEE Data Engineering Bulletin, 2023.
SecureBoost: A Lossless Federated Learning Framework [pdf]
Kewei Cheng, Tao Fan, Yilun Jin, Yang Liu, Tianjian Chen, Qiang Yang.
In IEEE Intelligent Systems, 2021.
Deep Convolutional Neural Network based Medical Concept Normalization [pdf]
Guojie Song, Qingqing Long, Yi Luo, Yiming Wang, Yilun Jin.
In IEEE Transactions on Big Data, 2020.

SecureBoost: A Lossless Federated Learning Framework [pdf]
Kewei Cheng, Tao Fan, Yilun Jin, Yang Liu, Tianjian Chen, Qiang Yang.
In The 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML-IJCAI’19).

(In Chinese) Chapter 6: Differential Privacy (差分隐私) and Chapter 8: Federated Learning (联邦学习) [purchase link]
In Privacy-Preserving Computing, Kai Chen and Qiang Yang, Publishing House of Electronics Industry, China, 2022.