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Q. Chen, X. Geng, C. Rosset, C. Buractaon, J. Lu, T. Shen, K. Zhou, C. Xiong, Y. Gong, P. Bennett, N. Craswell, X. Xie, F. Yang, B. Tower, N. Rao, …, and Zhang, C. “MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels”. ACM on Web Conference 2024.
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Y. Chen, R. Zheng, Q. Chen*, S. Xu, Q. Zhang, X. Wu, W. Han, H. Yuan, M. Li, Y. Wang, J. Li, F. Yang, H. Sun, W. Deng, F. Sun, Q.Zhang, and M. Yang. “OneSparse: A Unified System for Multi-index Vector Search”. ACM Web Conference 2024. Oral Presentation.
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H. Zhang, Y. Wang, Q. Chen, R. Chang, T. Zhang, Z. Miao, Y. Hou, Y. Ding, X. Miao, H. Wang, B. Pang, Y. Zhan, H. Sun, W. Deng, Q. Zhang, F. Yang, X. Xie, M. Yang, and B. Cui. “Model-enhanced Vector Index”. NeurIPS 2023.
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Y. Xu, H. Liang, J. Li, S. Xu, Q. Chen*, Q. Zhang, C. Li*, Z. Yang, F. Yang, Y. Yang, P. Cheng, M. Yang. “SPFresh: Incremental In-Place Update for Billion-Scale Vector Search”. ACM SOSP 2023.
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X. Tang, Y. Wang, T. Cao, L. Zhang, Q. Chen, D. Cai, Y. Liu and M. Yang. “LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and Table Lookup”. ACM MobiCom 2023.
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Q. Zhang, S. Xu, Q. Chen*, G. Sui, J. Xie, Z. Cai, Y. Chen, Y. He, Y. Yang, F. Yang and M. Yang. “VBASE: Unifying Online Vector Similarity Search and Relational Queries via Relaxed Monotonicity”. USENIX OSDI 2023.
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Z. Qiu, J. Yang, J. Zhang, C. Li, X. Ma, Q. Chen, M. Yang. and Y. Xu. “FrozenHot Cache: Rethinking Cache Management for Modern Hardware”. EuroSys 2023.
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Y. Wang, Y. Hou, H. Wang, Z. Miao, S. Wu, H. Sun, Q. Chen, Y. Xia, C. Chi, G. Zhao, Z. Liu, X. Xie, H. Sun, W. Deng, Q. Zhang, M. Yang. “A Neural Corpus Indexer for Document Retrieval”. NeurIPS 2022. Outstanding Paper Award.
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S. Xiao, Z. Liu, W. Han, J. Zhang, D. Lian, Y. Gong, Q. Chen, F. Yang, H. Sun, Y. Shao, D. Deng, Q. Zhang, and X. Xie, “Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings”. ACM SIGIR, 2022.
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Y. Wang, L. Xiong, M. Zhang, H. Xue, Q. Chen, Y. Yang, Y. Tong, C. Huang, and B. Xu, “Heat-RL: Online Model Selection for Streaming Time-Series Anomaly Detection”.CoLLAs, 2022.
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H. Simhadri, G. Williams, M. Aumüller, M. Douze, A. Babenko, D. Baranchuk, Q. Chen, L. Hosseini, R. Krishnaswamny, G. Srinivasa, S. Subramanya, and J. Wang, “Results of the NeurIPS’21 Challenge on Billion-Scale Approximate Nearest Neighbor Search”. Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, PMLR 176:177-189.
- Q. Chen, B. Zhao, H. Wang, M. Li, Z. Li, M. Yang, and J. Wang, “SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search”. NeurIPS, 2021. Spotlight Presentation.
- X. Shan, C. Liu, Y. Xia, Q. Chen, Y. Zhang, K. Ding, Y. Liang, A. Luo, and Y. Luo, “GLOW: Global Weighted Self-Attention Network for Web Search”. IEEE International Conference on Big Data, 2021.
- Z. Luo, L. Zhao, W. Cheng, S. Chen, Q. Chen, H. Xue, H. Wang, C. Liu, M. Yang, and L. Zhang, “Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning”. WWW, 2021.
- Y. Zhang, S. Setty, Q. Chen, L. Zhou and L. Alvisi, “Byzantine ordered consensus without Byzantine oligarchy”. USENIX OSDI, 2020. Jay Lepreau Best Paper Award.
- C. Liang, H. Xue, M. Yang, L. Zhou, L. Zhu, Z. Li, Z. Wang, Q. Chen, and Q. Zhang, “AutoSys: The Design and Operation of Learning-Augmented Systems”. USENIX ATC, 2020.
- L. Sha, C. Shi, Q. Chen, L. Zhang and H. Wang, “Estimating Minimum Operation Steps via Memory-based Recurrent Calculation Network“, IJCNN, 2020.
- Y. Lu, Y. Shu, X. Tan, Y. Liu, M. Zhou, Q. Chen, and D. Pei, “Collaborative Learning of Human Behavior: An Empirical Study on Location Prediction”, Proc.of the 4th ACM/IEEE Symposium on Edge Computing(SEC), 2019.
- C. Shi, Q. Chen, L. Sha, H. Xue, S. Li, H. Wang and L. Zhang. “We Know What You Will Ask: A Dialogue System for Multi-Intent Switch and Prediction”. NLPCC, 2019.
- C. Shi, Q. Chen, L. Sha, S. Li, X. Sun, H. Wang, and L. Zhang, “Auto-dialabel: Labeling dialogue data with unsupervised learning”. Proc. of the 2018 conference on empirical methods in natural language processing (EMNLP), 2018.
- H. Liu, Z. Huang, Q. Chen, M. Li, Y. Fu, and L. Zhang, “Fast Clustering with Flexible Balance Constraints”. IEEE International Conference on Big Data, 2018.
- Q. Chen, J. Yao, and Z. Xiao, “PISCES: Optimizing Multi-job Application Execution in MapReduce”. IEEE Transactions on Cloud Computing (TCC), 2016.
- W. Song, T. Gkountouvas, K. Birman, Q. Chen, and Z. Xiao, “The Freeze-Frame File System”. Proc. of the ACM Symposium on Cloud Computing (SoCC), 2016.
- C. Huang, Q. Chen, Z. Wang, R. Power, J. Ortiz, J. Li, and Z. Xiao, “Spartan: A distributed Array Framework with Smart Tiling”. USENIX ATC, 2015.
- Q. Chen, J. Yao, and Z. Xiao, “LIBRA: Lightweight Data Skew Mitigation in MapReduce”. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2015.
- Q. Chen, Y. Liao, C. Mitchell, J. Li, and Z. Xiao, “Building Scalable Multimedia Search Engine Using Infiniband”. USENIX HotCloud, 2014.
- Q. Chen, C. Liu, and Z. Xiao, “Improving MapReduce Performance Using Smart Speculative Execution Strategy”. IEEE Transactions on Computers (TC), 2014.
- Z. Xiao, Q. Chen, and H. Luo, “Automatic Scaling of Internet Applications for Cloud Computing Services”. IEEE Transactions on Computers (TC), 2014.
- W. Song, Z. Xiao, Q. Chen, and H. Luo, “Adaptive Resource Provisioning for the Cloud Using Online Bin Packing”. IEEE Transactions on Computers (TC), 2014.
- Z. Xiao, W. Song, and Q. Chen, “Dynamic Resource Allocation using Virtual Machines for Cloud Computing Environment”. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2013.