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2020 – today
- 2024
[j32]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 Comput. Surv. 56(8): 191:1-191:39 (2024)- [j31]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. Proc. ACM Manag. Data 2(3): 174 (2024) - [j30]Shihong Gao, Yiming Li, Yanyan Shen, Yingxia Shao, Lei Chen:
ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs. Proc. VLDB Endow. 17(5): 1060-1072 (2024) - [j29]Zhiyuan Li, Xun Jian, Yue Wang, Yingxia Shao, Lei Chen:
DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning. Proc. VLDB Endow. 17(6): 1364-1376 (2024) - [j28]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. VLDB J. 33(3): 833-857 (2024) - [j27]Ang Li, Yawen Li, Yingxia Shao:
Federated learning for supervised cross-modal retrieval. World Wide Web (WWW) 27(4): 41 (2024) - [c59]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: 18234-18242 - [c58]Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian:
Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval. ACL (1) 2024: 3490-3500 - [c57]Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu:
Distribution-Aware Diversification for Personalized Re-ranking in Recommendation. APWeb/WAIM (2) 2024: 65-81 - [c56]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: 3042-3055 - [c55]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 Multimedia 2024: 3917-3925 - [c54]Xizhi Gu, Hongzheng Li, Shihong Gao, Xinyan Zhang, Lei Chen, Yingxia Shao:
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training. ECML/PKDD (3) 2024: 250-266 - [c53]Duokang Wang, Linmei Hu, Rui Hao, Yingxia Shao, Xin Lv, Liqiang Nie, Juanzi Li:
Let Me Show You Step by Step: An Interpretable Graph Routing Network for Knowledge-based Visual Question Answering. SIGIR 2024: 1984-1994 - [i44]Linmei Hu, Hongyu He, Duokang Wang, Ziwang Zhao, Yingxia Shao, Liqiang Nie:
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model. CoRR abs/2403.07581 (2024) - [i43]Yuanhao Zeng, Min Wang, Yihang Wang, Yingxia Shao:
Token-Efficient Leverage Learning in Large Language Models. CoRR abs/2404.00914 (2024) - [i42]Jinqing Lian, Xinyi Liu, Yingxia Shao, Yang Dong, Ming Wang, Zhang Wei, Tianqi Wan, Ming Dong, Hailin Yan:
ChatBI: Towards Natural Language to Complex Business Intelligence SQL. CoRR abs/2405.00527 (2024) - [i41]Xizhi Gu, Hongzheng Li, Shihong Gao, Xinyan Zhang, Lei Chen, Yingxia Shao:
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training. CoRR abs/2406.04938 (2024) - [i40]Chaofan Li, Yingxia Shao, Zheng Liu:
SEA-SQL: Semantic-Enhanced Text-to-SQL with Adaptive Refinement. CoRR abs/2408.04919 (2024) - [i39]Rui Wang, Mengshi Qi, Yingxia Shao, Anfu Zhou, Huadong Ma:
Adversarial Contrastive Learning Based Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation. CoRR abs/2408.08488 (2024) - [i38]Yuanhao Zeng, Fei Ren, Xinpeng Zhou, Yihang Wang, Yingxia Shao:
DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models. CoRR abs/2408.10841 (2024) - [i37]Chaofan Li, Minghao Qin, Shitao Xiao, Jianlyu Chen, Kun Luo, Yingxia Shao, Defu Lian, Zheng Liu:
Making Text Embedders Few-Shot Learners. CoRR abs/2409.15700 (2024) - 2023
- [j26]Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen:
DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU. Proc. ACM Manag. Data 1(2): 166:1-166:24 (2023) - [j25]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. Proc. VLDB Endow. 16(13): 4282-4295 (2023) - [j24]Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui:
Experimental Analysis of Large-scale Learnable Vector Storage Compression. Proc. VLDB Endow. 17(4): 808-822 (2023) - [j23]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. IEEE Trans. Knowl. Data Eng. 35(2): 1721-1733 (2023) - [j22]Ang Li, Yawen Li, Yingxia Shao, Bingyan Liu:
Multi-View Scholar Clustering With Dynamic Interest Tracking. IEEE Trans. Knowl. Data Eng. 35(9): 9671-9684 (2023) - [j21]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. VLDB J. 32(4): 717-736 (2023) - [c52]Ziwei Chen, Linmei Hu, Weixin Li, Yingxia Shao, Liqiang Nie:
Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection. ACL (1) 2023: 627-638 - [c51]Zheng Liu, Shitao Xiao, Yingxia Shao, Zhao Cao:
RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. ACL (1) 2023: 2635-2648 - [c50]Ziwang Zhao, Linmei Hu, Hanyu Zhao, Yingxia Shao, Yequan Wang:
Knowledgeable Parameter Efficient Tuning Network for Commonsense Question Answering. ACL (1) 2023: 9051-9063 - [c49]Zihong Wang, Yingxia Shao, Jiyuan He, Jinbao Liu, Shitao Xiao, Tao Feng, Ming Liu:
Diversity-aware Deep Ranking Network for Recommendation. CIKM 2023: 2564-2573 - [c48]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 - [c47]Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao, Defu Lian, Zhao Cao:
LibVQ: A Toolkit for Optimizing Vector Quantization and Efficient Neural Retrieval. SIGIR 2023: 3095-3099 - [e1]Amr El Abbadi, Gillian Dobbie, Zhiyong Feng, Lu Chen, Xiaohui Tao, Yingxia Shao, Hongzhi Yin:
Database Systems for Advanced Applications. DASFAA 2023 International Workshops - BDMS 2023, BDQM 2023, GDMA 2023, BundleRS 2023, Tianjin, China, April 17-20, 2023, Proceedings. Lecture Notes in Computer Science 13922, Springer 2023, ISBN 978-3-031-35414-4 [contents] - [i36]Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao:
RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models. CoRR abs/2305.02564 (2023) - [i35]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. CoRR abs/2309.12239 (2023) - [i34]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. CoRR abs/2310.10998 (2023) - [i33]Runze Fang, Yawen Li, Yingxia Shao, Zeli Guan, Zhe Xue:
Entity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion. CoRR abs/2311.00300 (2023) - [i32]Weikang Chen, Junping Du, Yingxia Shao, Jia Wang, Yangxi Zhou:
Dynamic Fair Federated Learning Based on Reinforcement Learning. CoRR abs/2311.00959 (2023) - [i31]Peiyu Liu, Junping Du, Yingxia Shao, Zeli Guan:
Relation Extraction Model Based on Semantic Enhancement Mechanism. CoRR abs/2311.02564 (2023) - [i30]Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui:
Experimental Analysis of Large-scale Learnable Vector Storage Compression. CoRR abs/2311.15578 (2023) - [i29]Chaofan Li, Zheng Liu, Shitao Xiao, Yingxia Shao:
Making Large Language Models A Better Foundation For Dense Retrieval. CoRR abs/2312.15503 (2023) - 2022
- [j20]Shitao Xiao, Yingxia Shao, Yawen Li, Hongzhi Yin, Yanyan Shen, Bin Cui:
LECF: recommendation via learnable edge collaborative filtering. Sci. China Inf. Sci. 65(1) (2022) - [j19]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. Proc. VLDB Endow. 15(8): 1619-1631 (2022) - [j18]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. Proc. VLDB Endow. 15(9): 1937-1950 (2022) - [j17]Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang:
CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. IEEE Trans. Knowl. Data Eng. 34(9): 4119-4132 (2022) - [c46]Runze Fang, Junping Du, Yingxia Shao, Zeli Guan:
A Relational Triple Extraction Method Based on Feature Reasoning for Technological Patents. CCIS 2022: 501-505 - [c45]Yuxin Liu, Yawen Li, Yingxia Shao, Zeli Guan:
Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property. CCIS 2022: 506-510 - [c44]Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui:
Scalable Graph Sampling on GPUs with Compressed Graph. CIKM 2022: 2383-2392 - [c43]Shitao Xiao, Zheng Liu, Yingxia Shao, Zhao Cao:
RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder. EMNLP 2022: 538-548 - [c42]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). ICDE 2022: 1561-1562 - [c41]Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Bhuvan Middha, Fangzhao Wu, Xing Xie:
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop. KDD 2022: 4215-4225 - [c40]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: 4493-4501 - [c39]Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, 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: 1513-1523 - [c38]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. SIGIR 2022: 2776-2789 - [c37]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: 286-296 - [i28]Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Chaozhuo Li, Yingxia Shao, Defu Lian, Xing Xie, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang:
Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. CoRR abs/2201.05409 (2022) - [i27]Jianjin Zhang, Zheng Liu, Weihao Han, Shitao Xiao, Ruicheng Zheng, Yingxia Shao, Hao Sun, Hanqing Zhu, Premkumar Srinivasan, Denvy Deng, Qi Zhang, Xing Xie:
Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search. CoRR abs/2202.06212 (2022) - [i26]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. CoRR abs/2202.09177 (2022) - [i25]Yuhui Wang, Junping Du, Yingxia Shao:
An Intellectual Property Entity Recognition Method Based on Transformer and Technological Word Information. CoRR abs/2203.10717 (2022) - [i24]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. CoRR abs/2203.16123 (2022) - [i23]Suyu Ouyang, Yingxia Shao, Junping Du, Ang Li:
Scientific and Technological Text Knowledge Extraction Method of based on Word Mixing and GRU. CoRR abs/2203.17079 (2022) - [i22]Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Denvy Deng, Qi Zhang, Xing Xie:
Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings. CoRR abs/2204.00185 (2022) - [i21]Suyu Ouyang, Yingxia Shao, Ang Li:
Retrieval of Scientific and Technological Resources for Experts and Scholars. CoRR abs/2204.06142 (2022) - [i20]Yuhui Wang, Yingxia Shao, Ang Li:
Research on Intellectual Property Resource Profile and Evolution Law. CoRR abs/2204.06221 (2022) - [i19]Zheng Liu, Yingxia Shao:
RetroMAE: Pre-training Retrieval-oriented Transformers via Masked Auto-Encoder. CoRR abs/2205.12035 (2022) - [i18]Jia Wang, Junping Du, Yingxia Shao, Ang Li:
Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon. CoRR abs/2206.02160 (2022) - [i17]Xingchen Liu, Yawen Li, Yingxia Shao, Ang Li, Jian Liang:
A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT. CoRR abs/2206.02389 (2022) - [i16]Jie Gao, Junping Du, Yingxia Shao, Ang Li, Zeli Guan:
Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency. CoRR abs/2206.10952 (2022) - [i15]Chengjie Ma, Junping Du, Yingxia Shao, Ang Li, Zeli Guan:
A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network. CoRR abs/2207.00432 (2022) - [i14]Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Ming-Hsuan Yang, Bin Cui:
Diffusion Models: A Comprehensive Survey of Methods and Applications. CoRR abs/2209.00796 (2022) - [i13]Runze Fang, Junping Du, Yingxia Shao, Zeli Guan:
A Relational Triple Extraction Method Based on Feature Reasoning for Technological Patents. CoRR abs/2210.03291 (2022) - [i12]Yuxin Liu, Yawen Li, Yingxia Shao, Zeli Guan:
Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property. CoRR abs/2210.05947 (2022) - [i11]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. CoRR abs/2211.00216 (2022) - [i10]Xinyi Gao, Wentao Zhang, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin:
Efficient Graph Neural Network Inference at Large Scale. CoRR abs/2211.00495 (2022) - 2021
- [j16]Jiaxu Liu, Yingxia Shao, Sen Su:
Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks. Data Sci. Eng. 6(3): 249-264 (2021) - [j15]Zeyu Liang, Junping Du, Yingxia Shao, Houye Ji:
Gated Graph Neural Attention Networks for abstractive summarization. Neurocomputing 431: 128-136 (2021) - [j14]Yingxia Shao, Xupeng Li, Yiru Chen, Lele Yu, Bin Cui:
Sys-TM: A Fast and General Topic Modeling System. IEEE Trans. Knowl. Data Eng. 33(6): 2790-2802 (2021) - [j13]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. VLDB J. 30(5): 769-797 (2021) - [c36]Yongqiang Ma, Yingxia Shao, Zhe Xue, Ziqiang Yu:
Urban Fatigue Driving Prediction With Federated Learning. CCIS 2021: 47-51 - [c35]Xiaomeng Chen, Yingxia Shao, Zhe Xue, Ziqiang Yu:
Multi-Modal COVID-19 Discovery With Collaborative Federated Learning. CCIS 2021: 52-56 - [c34]Zeli Guan, Yawen Li, Zhe Xue, Yuxin Liu, Hongrui Gao, Yingxia Shao:
Federated Graph Neural Network for Cross-graph Node Classification. CCIS 2021: 418-422 - [c33]Xin Xia, Hongzhi Yin, Junliang Yu, Yingxia Shao, Lizhen Cui:
Self-Supervised Graph Co-Training for Session-based Recommendation. CIKM 2021: 2180-2190 - [c32]Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie:
Matching-oriented Embedding Quantization For Ad-hoc Retrieval. EMNLP (1) 2021: 8119-8129 - [c31]Xingyu Yao, Yingxia Shao, Bin Cui, Lei Chen:
UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling. ICDE 2021: 516-527 - [c30]Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang:
CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). ICDE 2021: 2330-2331 - [c29]Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang:
DeGNN: Improving Graph Neural Networks with Graph Decomposition. KDD 2021: 1223-1233 - [c28]Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui:
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. SIGMOD Conference 2021: 563-576 - [c27]Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui:
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. SIGMOD Conference 2021: 2262-2270 - [c26]Yingxia Shao, Hailin Jiang, Hongli Zhao:
Radio resource management algorithm for urban rail transit communication system based on Stackelberg game. VTC Spring 2021: 1-5 - [c25]Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao, Nguyen Quoc Viet Hung:
Heterogeneous Hypergraph Embedding for Graph Classification. WSDM 2021: 725-733 - [i9]Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Xing Xie:
Training Microsoft News Recommenders with Pretrained Language Models in the Loop. CoRR abs/2102.09268 (2021) - [i8]Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie:
Search-oriented Differentiable Product Quantization. CoRR abs/2104.07858 (2021) - [i7]Xin Xia, Hongzhi Yin, Junliang Yu, Yingxia Shao, Lizhen Cui:
Self-Supervised Graph Co-Training for Session-based Recommendation. CoRR abs/2108.10560 (2021) - [i6]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Efficient Diversity-Driven Ensemble for Deep Neural Networks. CoRR abs/2112.13316 (2021) - 2020
- [b1]Yingxia Shao, Bin Cui, Lei Chen:
Large-scale Graph Analysis: System, Algorithm and Optimization. Springer 2020, ISBN 978-981-15-3927-5, pp. 1-146 - [j12]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Snapshot boosting: a fast ensemble framework for deep neural networks. Sci. China Inf. Sci. 63(1): 112102 (2020) - [j11]Yingxia Shao, Yanyan Shen, Bin Cui, Jeffrey Xu Yu:
DASFAA 20202 Special Issue Editorial. Data Sci. Eng. 5(4): 331-332 (2020) - [j10]Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui:
SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. VLDB J. 29(5): 945-972 (2020) - [c24]Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui:
Efficient Automatic CASH via Rising Bandits. AAAI 2020: 4763-4771 - [c23]Jiaxu Liu, Yingxia Shao, Sen Su:
Multiple Local Community Detection via High-Quality Seed Identification. APWeb/WAIM (1) 2020: 37-52 - [c22]Minxu Zhang, Yingxia Shao, Kai Lei, Yuesheng Zhu, Bin Cui:
Densely-Connected Transformer with Co-attentive Information for Matching Text Sequences. APWeb/WAIM (2) 2020: 230-244 - [c21]Mubashir Imran, Hongzhi Yin, Tong Chen, Yingxia Shao, Xiangliang Zhang, Xiaofang Zhou:
Decentralized Embedding Framework for Large-Scale Networks. DASFAA (3) 2020: 425-441 - [c20]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Efficient Diversity-Driven Ensemble for Deep Neural Networks. ICDE 2020: 73-84 - [c19]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: 3304-3314 - [c18]Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui:
Reliable Data Distillation on Graph Convolutional Network. SIGMOD Conference 2020: 1399-1414 - [c17]Yingxia Shao, Shiyue Huang, Xupeng Miao, Bin Cui, Lei Chen:
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs. SIGMOD Conference 2020: 1797-1812 - [i5]Xingyu Yao, Yingxia Shao, Bin Cui, Lei Chen:
UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling. CoRR abs/2010.04895 (2020) - [i4]Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao, Nguyen Quoc Viet Hung:
Heterogeneous Hypergraph Embedding for Graph Classification. CoRR abs/2010.10728 (2020) - [i3]Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui:
Efficient Automatic CASH via Rising Bandits. CoRR abs/2012.04371 (2020)
2010 – 2019
- 2019
- [j9]Zhonghong Ou, Yunfeng Liu, Huihui Kong, Meina Song, Yingxia Shao:
CNN Compression-Recovery Framework via Rank Allocation Decomposition With Knowledge Transfer. IEEE Access 7: 105470-105478 (2019) - [j8]Yingxia Shao, Jialin Liu, Shuyang Shi, Yuemei Zhang, Bin Cui:
Fast De-anonymization of Social Networks with Structural Information. Data Sci. Eng. 4(1): 76-92 (2019) - [j7]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. Proc. VLDB Endow. 12(11): 1357-1370 (2019) - [c16]Jinyang Gao, Junjie Yao, Yingxia Shao:
Towards Reliable Learning for High Stakes Applications. AAAI 2019: 3614-3621 - [c15]Huanran Xue, Jiawei Jiang, Yingxia Shao, Bin Cui:
FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. APWeb/WAIM (2) 2019: 27-41 - [c14]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: 1953-1962 - [c13]Haobo Sun, Yingxia Shao, Jiawei Jiang, Bin Cui, Kai Lei, Yu Xu, Jiang Wang:
Sparse Gradient Compression for Distributed SGD. DASFAA (2) 2019: 139-155 - [c12]Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen:
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. ICDE 2019: 614-625 - [c11]Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao:
PS2: Parameter Server on Spark. SIGMOD Conference 2019: 376-388 - [i2]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. CoRR abs/1907.01882 (2019) - 2018
- [c10]Zichen Wang, Tian Li, Yingxia Shao, Bin Cui:
CUTE: Querying Knowledge Graphs by Tabular Examples. APWeb/WAIM (1) 2018: 461-465 - [c9]Lele Yu, Lingyu Wang, Yingxia Shao, Long Guo, Bin Cui:
GLM+: An Efficient System for Generalized Linear Models. BigComp 2018: 293-300 - [c8]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: 1753-1754 - [i1]Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen:
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. CoRR abs/1812.06410 (2018) - 2017
- [j6]Zhipeng Zhang, Yingxia Shao, Bin Cui, Ce Zhang:
An Experimental Evaluation of SimRank-based Similarity Search Algorithms. Proc. VLDB Endow. 10(5): 601-612 (2017) - [j5]Lele Yu, Bin Cui, Ce Zhang, Yingxia Shao:
LDA*: A Robust and Large-scale Topic Modeling System. Proc. VLDB Endow. 10(11): 1406-1417 (2017) - [j4]Yingxia Shao, Kai Lei, Lei Chen, Zi Huang, Bin Cui, Zhongyi Liu, Yunhai Tong, Jin Xu:
Fast Parallel Path Concatenation for Graph Extraction. IEEE Trans. Knowl. Data Eng. 29(10): 2210-2222 (2017) - 2016
- [c7]Xiaogang Shi, Bin Cui, Yingxia Shao, Yunhai Tong:
Tornado: A System For Real-Time Iterative Analysis Over Evolving Data. SIGMOD Conference 2016: 417-430 - 2015
- [j3]Yingxia Shao, Bin Cui, Lei Chen, Mingming Liu, Xing Xie:
An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs. Proc. VLDB Endow. 8(8): 838-849 (2015) - [j2]Yingxia Shao, Bin Cui, Lin Ma:
PAGE: A Partition Aware Engine for Parallel Graph Computation. IEEE Trans. Knowl. Data Eng. 27(2): 518-530 (2015) - [j1]Ning Xu, Bin Cui, Lei Chen, Zi Huang, Yingxia Shao:
Heterogeneous Environment Aware Streaming Graph Partitioning. IEEE Trans. Knowl. Data Eng. 27(6): 1560-1572 (2015) - [c6]Hongzhi Yin, Xiaofang Zhou, Yingxia Shao, Hao Wang, Shazia Wasim Sadiq:
Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation. CIKM 2015: 1631-1640 - [c5]Lele Yu, Yingxia Shao, Bin Cui:
Exploiting Matrix Dependency for Efficient Distributed Matrix Computation. SIGMOD Conference 2015: 93-105 - 2014
- [c4]Yingxia Shao, Lei Chen, Bin Cui:
Efficient cohesive subgraphs detection in parallel. SIGMOD Conference 2014: 613-624 - [c3]Yingxia Shao, Bin Cui, Lei Chen, Lin Ma, Junjie Yao, Ning Xu:
Parallel subgraph listing in a large-scale graph. SIGMOD Conference 2014: 625-636 - 2013
- [c2]Yingxia Shao, Junjie Yao, Bin Cui, Lin Ma:
PAGE: a partition aware graph computation engine. CIKM 2013: 823-828 - [c1]Xiaogang Shi, Yanfei Lv, Yingxia Shao, Bin Cui:
bCATE: A Balanced Contention-Aware Transaction Execution Model for Highly Concurrent OLTP Systems. WAIM 2013: 769-780
Coauthor Index
[j32] [c56] [j25] [j24] [j23] [j21] [i35] [i34] [i30] [j20] [j19] [j17] [c44] [c42] [i24] [i14] [i11] [i10] [j14] [j13] [c31] [c30] [c29] [c28] [c27] [i6] [b1] [j12] [j11] [j10] [c24] [c22] [c20] [c19] [c18] [c17] [i5] [i3] [j8] [j7] [c15] [c13] [c11] [i2] [c10] [c9] [c8] [j6] [j5] [j4] [c7] [j3] [j2] [j1] [c5] [c4] [c3] [c2] [c1]
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