Yingxia Shao

Yingxia Shao

Professor at SCS, BUPT

Publications

2024

  1. Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen. Distributed Graph Neural Network Training: A Survey, ACM Computing Surveys, 2024
  2. Shihong Gao, Yiming Li, Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen. SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement, SIGMOD 2024
  3. Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui. Experimental Analysis of Large-scale Learnable Vector Storage Compression, VLDB 2024
  4. Shihong Gao, Yiming Li, Yanyan Shen, Yingxia Shao, Lei Chen. ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs, VLDB 2024
  5. Zhiyuan Li, Xun Jian, Yue Wang, Yingxia Shao, Lei Chen. Accelerating GNN Training with Data and Hardware Aware Execution Planning, VLDB 2024
  6. Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin, Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation, ICDE 2024
  7. Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang, How good are machine learning clouds? Benchmarking two snapshots over 5 years, VLDBJ 2024
  8. Linmei Hu, Hongyu He, Duokang Wang, Ziwang Zhao, Yingxia Shao, Liqiang Nie, LLM vs Small Model? Large Language Model based Text Augmentation Enhanced Personality Detection Model, AAAI 2024
  9. Duokang Wang, Linmei Hu, Rui Hao, Yingxia Shao, Xin Lv, Liqiang Nie and Juanzi Li, Let Me Show You Step by Step: An Interpretable Graph Routing Network for Knowledge-based Visual Question Answering, SIGIR 2024
  10. Linmei Hu, Duokang Wang, Yiming Pan, Jifan Yu, Yingxia Shao, Chong Feng, Liqiang Nie, NovaChart: A Large-scale Dataset towards Chart Understanding and Generation of Multimodal Large Language Models, ACM MM 2024
  11. Zheng Liu, Chaofan Li, Shitao Xiao, Yingxia Shao, Defu Lian, LLAMA2VEC: Unsupervised Adaptation of Large Language Models for Dense Retrieval, ACL 2024
  12. Xizhi Gu, Hongzheng Li, Shihong Gao, Xinyan Zhang, Lei Chen, Yingxia Shao, SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training, ECMLPKDD 2024
  13. Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu, Distribution-aware Diversification for Personalized Re-ranking in Recommendation, APWeb-WAIM 2024

2023

  1. Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen. DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU, SIGMOD 2023
  2. Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang. A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture, TKDE 2023
  3. Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui. P2CG: a Privacy Preserving Collaborative Graph Neural Network Training Framework, VLDBJ 2023
  4. Ang Li, Yawen Li, Yingxia Shao, Bingyan Liu. Multi-View Scholar Clustering With Dynamic Interest Tracking, TKDE 2023
  5. Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian, Zhao Cao. LibVQ: A Toolkit For Optimizing Vector Quantization And Efficient Neural Retrieval (Demo), SIGIR 2023
  6. Ziwei Chen, Linmei Hu, Weixin Li, Yingxia Shao, Liqiang Nie. Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection. ACL 2023
  7. Zheng Liu, Shitao Xiao, Yingxia Shao, Zhao Cao. RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. ACL 2023
  8. Ziwang Zhao, Linmei Hu, Hanyu Zhao, Yingxia Shao, Yequan Wang. Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering. ACL 2023
  9. Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu, Shitao Xiao, Tao Feng, Ming Liu. Diversity-aware Deep Ranking Network for Recommendation. CIKM 2023
  10. Jinqing Lian, Xinyi Zhang, Yingxia Shao, Zenglin Pu, Qingfeng Xiang, Yawen Li, Bin Cui. ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems. VLDB 2023
  11. Jingshu Peng, Zhao Chen, Yingxia Shao, Yanyan Shen, Lei Chen, Jiannong Cao. Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks (Extended Abstract). IJCAI 2023: 6480-6485

2022

  1. Hongzheng Li, Yingxia Shao, Junping Du, Bin Cui, Lei Chen, An I/O-Efficient Disk-based Graph System for Scalable Second-Order Random Walk of Large Graphs, VLDB 2022
  2. Jingshu Peng, Zhao Chen, Yingxia Shao, Yanyan Shen, Lei Chen, Jiannong Cao. Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks, VLDB 2022 (Best Regular Research Paper)
  3. Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Fangzhao Wu, Bhuvan Middha, Xing Xie. Training Large-Scale News Recommenders with Pretrained Language Models in the Loop, KDD 2022
  4. Jianjin Zhang, Zheng Liu, Weihao Han, Shitao Xiao, Ruicheng Zheng, Yingxia Shao, Hao Sun, Hanqing zhu, Premkumar Srinivasan, Weiwei Deng, Qi Zhang, Xing Xie. Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search, KDD 2022
  5. Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Yingxia Shao, Defu Lian, Chaozhuo Li, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang, Xing Xie, Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval, WWW 2022
  6. Shitao Xiao, Zheng Liu, Weihao Han, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Xing Xie. Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings, SIGIR 2022
  7. Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang and Chuan Shi. Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network, SIGIR 2022
  8. Shitao Xiao, Yingxia Shao, Yawen Li, Hongzhi Yin, Yanyan Shen, Bin Cui, LECF: Recommendation via Learnable Edge Collaborative Filtering, Sci China Inf Sci, 2022, 65: 112101
  9. Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang. A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture, ICDE 2022 (TKDE Poster)
  10. Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui. Scalable Graph Sampling on GPUs with Compressed Graph, CIKM 2022.
  11. Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao. RetroMAE: Pre-training Retrieval-oriented Transformers via Masked Auto-Encoder, EMNLP 2022
  12. Xupeng Miao, Linxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang. CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs, 34(9):4119-4132, TKDE 2022

2021

  1. Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie. Matching-oriented Embedding Quantization For Ad-hoc Retrieval, EMNLP 2021
  2. Yingxia Shao, Shiyue Huang, Yawen Li, Xupeng Miao, Bin Cui, Lei Chen, Memory-Aware Framework for Fast and Scalable Second-Order Random Walk over Billion-Edge Natural Graphs, VLDBJ 2021
  3. Jiaxu Liu, Yingxia Shao, Sen Su, Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks, Data Science and Engineering, 2021
  4. Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui, VF^2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning, SIGMOD 2021
  5. Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui, Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce, SIGMOD 2021
  6. Xingyu Yao, Yingxia Shao, Bin Cui, Lei Chen, UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling, ICDE 2021
  7. Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, wei min, Susie Xi Susie Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, et. al. DeGNN: Improving Graph Neural Networks with Graph Decomposition, KDD 2021
  8. Xupeng Miao, Linxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang, CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs, ICDE 2021 (TKDE Poster)
  9. Yingxia Shao, Xupeng Li, Yiru Chen, Lele Yu, Bin Cui, Sys-TM: A Fast and General Topic Modeling System, TKDE 2021
  10. Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao, Nguyen Quoc Viet Hung, Heterogeneous Hypergraph Embedding for Graph Classification, WSDM 2021
  11. Xin Xia, Hongzhi Yin, Junliang Yu, Yingxia Shao, Lizhen Cui. Self-Supervised Co-Training for Session-based Recommendation, CIKM 2021

2020

  1. Yingxia Shao, Shiyue Huang, Xupeng Miao, Bin Cui, Lei Chen, Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs, SIGMOD 2020
  2. Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui, Reliable Data Distillation on Graph Convolutional Network, SIGMOD 2020
  3. Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui, Efficient Diversity-Driven Ensemble for Deep Neural Networks, ICDE 2020
  4. Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui, Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript, ICML 2020
  5. Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui, Efficient Automatic CASH via Rising Bandits, AAAI 2020
  6. Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui, SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. The VLDB Journal (2020)
  7. Mubashir Imran, Hongzhi Yin, Tong Chen, Yingxia Shao, Xiangliang Zhang and Xiaofang Zhou, Decentralized Embedding Framework for Large-scale Networks, DASFAA 2020 (Best Student Paper Award)
  8. Jiaxu Liu, Yingxia Shao, Sen Su, Multiple Local Community Detection via High-Quality Seed Identification, APWeb-WAIM 2020
  9. Minxu zhang, Yingxia Shao, Kai Lei, Yuesheng Zhu, Bin Cui, Densely-connected Transformer with Co-attentive Information for Matching Text Sequences, APWeb-WAIM 2020
  10. Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui, Snapshot Boosting: A Fast Ensemble Framework for Deep Neural Networks. Sci China Inf Sci, 2020, 63(1): 112102

2019

  1. Yushun Dong, Yingxia Shao, Xiaotong Li, Sili Li, Lei Quan, Wei Zhang, Junping Du, Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model, CIKM 2019
  2. Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui. An Experimental Evaluation of Large Scale GBDT Systems. VLDB 2019
  3. Yingxia Shao, Jialin Liu, Shuyang Shi, Yuemei Zhang, Bin Cui. Fast De-anonymization of Social Networks with Structural Information, Data Science and Engineering, (2019) 4: 76.
  4. Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao. PS2: Parameter Server on Spark. SIGMOD 2019
  5. Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen. NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding, ICDE 2019
  6. Jinyang Gao, Junjie Yao, Yingxia Shao. Towards Reliable Learning for High Stakes Applications, AAAI 2019
  7. Haobao Sun, Yingxia Shao, Jiawei Jiang, Bin Cui, Kai Lei, Yu Xu, Jiang Wang. Sparse Gradient Compression for Distributed SGD, DASFAA 2019
  8. Huanran Xue, Jiawei Jiang, Yingxia Shao, Bin Cui. FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. APWeb-WAIM 2019

2018 and Early

  1. Zichen Wang, Tian Li, Yingxia Shao, Bin Cui. CUTE: Querying Knowledge Graphs by Tabular Examples (Demo), APWeb-WAIM, 2018
  2. Yingxia Shao, Kai Lei, Lei Chen, Zi Huang, Bin Cui, Zhongyi Liu, Yunhai Tong, Jin Xu, Fast Parallel Path Concatenation for Graph Extraction, ICDE 2018 (TKDE Poster)
  3. Lele Yu, Lingyu Wang, Yingxia Shao, Long Guo, Bin Cui. GLM+: An Efficient System for Generalized Linear Models, BigComp, 2018
  4. Lele Yu, Ce Zhang, Yingxia Shao, Bin Cui. LDA*: A Robust and Large-scale Topic Modeling System, PVLDB 10(11): 2017
  5. Yingxia Shao, Kai Lei, Lei Chen, Zi Huang, Bin Cui, Zhongyi Liu, Yunhai Tong, Jin Xu, Fast Parallel Path Concatenation for Graph Extraction, TKDE 2017
  6. Zhipeng Zhang, Yingxia Shao, Bin Cui, Ce Zhang. An Experimental Evaluation of SimRank based Similarity Search Algorithms, VLDB 2017
  7. Xiaogang Shi, Bin Cui, Yingxia Shao, Yunhai Tong, Tornado: A System For Real-Time Iterative Analysis Over Evolving Data, SIGMOD 2016
  8. Hongzhi Yin, Xiaofang Zhou, Yingxia Shao, Hao Wang, Shazia Sadiq, Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation, CIKM 2015
  9. Yingxia Shao, Bin Cui, Lei Chen, Mingming Liu, Xing Xie, An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs. PVLDB 2015
  10. Lele Yu, Yingxia Shao, Bin Cui, Exploiting matrix dependency for efficient distributed matrix computation. SIGMOD 2015
  11. Yingxia Shao, Bin Cui, Lin Ma, PAGE: A Partition Aware Engine for Parallel Graph Computation. TKDE 2015
  12. Ning Xu, Bin Cui, Lei Chen, Zi Huang, Yingxia Shao, Heterogeneous Environment Aware Streaming Graph Partitioning, TKDE, 2015
  13. Yingxia Shao, Bin Cui, Lei Chen, Lin Ma, Junjie Yao, Ning Xu, Parallel Subgraph Listing in a Large Scale Graph. SIGMOD 2014
  14. Yingxia Shao, Lei Chen, Bin Cui, Efficient Cohesive Subgraphs Detection in Parallel. SIGMOD 2014
  15. Yingxia Shao, Junjie Yao, Bin Cui, Lin Ma, PAGE: A Partition Aware Graph Computation Engine. CIKM 2013

Chinese Journals

  1. Jiaxin Yang, Junping Du, Yingxia Shao, Ang Li, Junqing Xi. Construction Method of Intellectual-property-oriented Scientific and Technological Resources Portrait. Ruan Jian Xue Bao/Journal of Software, 2022, 33(4):1439−1450 (in Chinese)
  2. Shitao Xiao, Yingxia Shao, Weiping Song, Bin Cui. Hybrid Score Function for Collaborative Filtering Recommendation, Computer Science, 2021, 48(3):113-118 (in Chinese)
  3. Jiang Jiawei, Fu Fangchen, Shao Yingxia, Cui Bin. Distributed Gradient Boosting Decision Tree Algorithm for High-dimensional and Multi-classification Problems. Ruan Jian Xue ao/Journal of Software, 2018,29(3):1−14 (in Chinese)
  4. Shi Shuyang, Zhang Zhipeng, Guo Long, Shao Yingxia, Cui Bin. Resume Activeness Prediction in Online Recruitment Scenarios. Journal of Frontiers of Computer Science and Technology, 2018, 12(5): 730-740 (in Chinese)
  5. Jialin Liu, Shuyang Shi, Yuemei Zhang, Yingxia Shao, Bin Cui. RoleMatch: An effective and efficient approach of graph deanonymization. Ruan Jian Xue Bao/Journal of Software, 2018,29(3):1−14 (in Chinese)
  6. Quanglong Huang, Yanxiang Huang, Yingxia Shao, Jia Meng, Xinqi Ren, Bin Cui, Shicong Feng. HybriG: A Distributed Architecture for Property Graph with Large Set of Multi-edges, Chinese Journal of Computers 2017,40(61) (in Chinese)
  7. Yingxia Shao, Bin Cui, Lin Ma, Hongzhi Yin, A Fast Sketch-based Approach of Top-k Closeness Centrality Search on Large Networks, Chinese Journal of Computers, 2016,39(10):1965-1978 (in Chinese)