An Efficient Fuzzy Rough Approach for Feature Selection. - Feifei Xu; Weiguo Pan; Lai Wei 001; Haizhou Du (RSKT, 2011)

Study of a Fuzzy Clustering Algorithm Based on Interval Value. - Haizhou Du (WISM (1), 2011)

A fuzzy clustering algorithm based on interval valued fuzzy sets. - Haizhou Du; Weiguo Pan (FSKD, 2012)

Robust Local Outlier Detection. - Haizhou Du; Shengjie Zhao 001; Daqiang Zhang 001 (ICDM Workshops, 2015)

Robust local outlier detection with statistical parameter for big data. - Jingsheng Lei; Teng Jiang; Kui Wu 001; Haizhou Du; Lin Zhu (Comput. Syst. Sci. Eng., 2015)

Novel clustering-based approach for Local Outlier Detection. - Haizhou Du; Shengjie Zhao 001; Daqiang Zhang 001; Jinsong Wu 001 (INFOCOM Workshops, 2016)

A Novel Text Feature Weight Calculation Method Applied to Power Field. - Haizhou Du; Zhengbo Chen; Qifen Li; Yongwen Yang (Trustcom/BigDataSE/ISPA, 2016)

Robust K-means algorithm with automatically splitting and merging clusters and its applications for surveillance data. - Jingsheng Lei; Teng Jiang; Kui Wu 001; Haizhou Du; Guokang Zhu; Zhaoqing Wang (Multim. Tools Appl., 2016)

MMDBC: Density-Based Clustering Algorithm for Mixed Attributes and Multi-dimension Data. - Haizhou Du; Wei Fang; Haining Huang; Shuqing Zeng (BigComp, 2018)

FASTBEE: A Fast and Self-Adaptive Clustering Algorithm Towards to Edge Computing. - Haizhou Du; Shuqing Zeng; Tingting Dou; Wei Fang; Yi Wang; Chenlu Zhang (CSCloud/EdgeCom, 2018)

Otterman: A Novel Approach of Spark Auto-tuning by a Hybrid Strategy. - Haizhou Du; Ping Han; Wei Chen; Yi Wang; Chenlu Zhang (ICSAI, 2018)

Hierarchical Gated Convolutional Networks with Multi-Head Attention for Text Classification. - Haizhou Du; Jingu Qian (ICSAI, 2018)

Octopus: Based on Congestion-aware Scheduling on Geo-distributed Big Data Analytics Cluster. - Haizhou Du; Keke Zhang; Zhenchen Yang (ICSAI, 2018)

Multi-Stage Mixed Attribute Outlier Detection Algorithm Based on Neighborhood Density Difference. - Haizhou Du; Wei Fang; Qing Liu; Zhenchen Yang; Xiaofeng Wang (BigCom, 2019)

Cheetah: A Dynamic Performance Optimization Approach on Heterogeneous Big Data Analytics Cluster. - Haizhou Du; Shaohua Zhang; Ping Han; Keke Zhang; Bin Xu (BigCom, 2019)

OctopusKing: A TCT-Aware Task Scheduling on Spark Platform. - Haizhou Du; Keke Zhang; Sheng Huang (ICPADS, 2019)

Hephaistos: A fast and distributed outlier detection approach for big mixed attribute data. - Haizhou Du; Wei Fang; Yi Wang (Intell. Data Anal., 2019)

A novel graph compression algorithm for data-intensive scientific networks. - Xiao Lin; Haizhou Du; Shenshen Chen (Int. J. High Perform. Comput. Netw., 2019)

Controllable Multi-Character Psychology-Oriented Story Generation. - Feifei Xu; Xinpeng Wang 001; Yunpu Ma; Volker Tresp; Yuyi Wang 001; Shanlin Zhou; Haizhou Du (CIKM, 2020)

Dawn: Co-programming Distributed Applications with Network Control. - Shuhe Wang; Dong Guo; Wei Jiang; Haizhou Du; Mingwei Xu (NAI@SIGCOMM, 2020)

Hawkeye: Adaptive Straggler Identification on Heterogeneous Spark Cluster With Reinforcement Learning. - Haizhou Du; Shaohua Zhang (IEEE Access, 2020)

MonkeyKing: Adaptive Parameter Tuning on Big Data Platforms with Deep Reinforcement Learning. - Haizhou Du; Ping Han; Qiao Xiang; Sheng Huang (Big Data, 2020)

Trident: Change Point Detection for Multivariate Time Series via Dual-Level Attention Learning. - Ziyi Duan; Haizhou Du; Yang Zheng (ACIIDS, 2021)

FLZip: An Efficient and Privacy-Preserving Framework for Cross-Silo Federated Learning. - Xiaojie Feng; Haizhou Du (iThings/GreenCom/CPSCom/SmartData/Cybermatics, 2021)

Symbiosis: A Novel Framework for Integrating Hierarchies from Knowledge Graph into Recommendation System. - Haizhou Du; Yue Tang (KSEM, 2021)

Stargazer: Toward efficient data analytics scheduling via task completion time inference. - Haizhou Du; Keke Zhang; Qiao Xiang (Comput. Electr. Eng., 2021)

Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression. - Haizhou Du; Xiaojie Feng; Qiao Xiang; Haoyu Liu (CoRR, 2021)

Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning. - Haizhou Du; Zong Yan; Qiao Xiang; Qinqing Zhan (CoRR, 2021)

Isomer: Transfer enhanced Dual-Channel Heterogeneous Dependency Attention Network for Aspect-based Sentiment Classification. - Yukun Cao; Yijia Tang; Ziyue Wei; ChengKun Jin; Zeyu Miao; Yixin Fang; Haizhou Du; Feifei Xu (CoRR, 2021)

XFinder: Detecting Unknown Anomalies in Distributed Machine Learning Scenario. - Haizhou Du; Shiwei Wang; Huan Huo (Frontiers Comput. Sci., 2021)

CPMAN: Change Point Detection Approach in Time Series Based on the Prediction of Multi-stage Attention Networks. - Haizhou Du; Ziyi Duan; Yang Zheng (Int. J. Artif. Intell. Tools, 2021)

Astrologer: Exploiting graph neural Hawkes process for event propagation prediction with spatio-temporal characteristics. - Haizhou Du; Yan Zhou; Yunpu Ma; Shiwei Wang (Knowl. Based Syst., 2021)

Orchestra: adaptively accelerating distributed deep learning in heterogeneous environments. - Haizhou Du; Sheng Huang; Qiao Xiang (CF, 2022)

Sailfish: A Fast Bayesian Change Point Detection Framework with Gaussian Process for Time Series. - Haizhou Du; Yang Zheng (ICANN (3), 2022)

Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings. - Ryan Yang; Haizhou Du; Andre Wibisono; Patrick Baker (MILCOM, 2022)

Finder: A novel approach of change point detection for multivariate time series. - Haizhou Du; Ziyi Duan (Appl. Intell., 2022)

Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions. - Haizhou Du; Ryan Yang; Yijian Chen; Qiao Xiang; Andre Wibisono; Wei Huang (CoRR, 2022)

Isomer: Transfer enhanced dual-channel heterogeneous dependency attention network for aspect-based sentiment classification. - Yukun Cao; Yijia Tang; Haizhou Du; Feifei Xu; Ziyue Wei; ChengKun Jin (Knowl. Based Syst., 2022)

Nostradamus: A novel event propagation prediction approach with spatio-temporal characteristics in non-Euclidean space. - Haizhou Du; Yan Zhou (Neural Networks, 2022)

Baileys: An Efficient Distributed Machine Learning Framework by Dynamic Grouping. - Chengdong Ni; Haizhou Du (ICMLC, 2023)

What Appears Suboptimal May Surprise You: A Fixed-Rate Scheduling Policy for Geo-Distributed CoFlows. - Haoyu Liu; Feiyan Ding; Yao Wang 022; Qiao Xiang; Jiwu Shu; Haizhou Du; Linghe Kong; Xue Liu 001 (ICPADS, 2023)

Toward a Unified Framework for Verifying and Interpreting Learning-Based Networking Systems. - Yangfan Huang; Yuling Lin; Haizhou Du; Yijian Chen; Haohao Song; Linghe Kong; Qiao Xiang; Qiang Li 045; Franck Le; Jiwu Shu (IWQoS, 2023)

A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data. - Haizhou Du; Chengdong Ni (CoRR, 2023)

Heterogeneous Reinforcement Learning Network for Aspect-Based Sentiment Classification With External Knowledge. - Yukun Cao; Yijia Tang; Haizhou Du; Feifei Xu; Ziyue Wei; ChengKun Jin (IEEE Trans. Affect. Comput., 2023)

An efficient federated learning framework for multi-channeled mobile edge network with layered gradient compression. - Haizhou Du; Yijian Chen; Xiaojie Feng; Qiao Xiang; Haoyu Liu (Comput. Networks, 2023)

An efficient joint framework for interacting knowledge graph and item recommendation. - Haizhou Du; Yue Tang; Zebang Cheng (Knowl. Inf. Syst., 2023)

Rethinking DNS Configuration Verification with a Distributed Architecture. - Yao Wang 022; Kexin Yu; Ziyi Wang; Kaiqiang Hu; Haizhou Du; Qiao Xiang; Xing Fang; Geng Li; Ruiting Zhou; Linghe Kong; Jiwu Shu (APNet, 2024)

DCCN-Informer: An Attention-Based Long Time Series Prediction Method for Power Load. - Rongkai Zhang 006; Haizhou Du; Xuewen Lv (BESC, 2024)

Causal Inference KGC: A Multi-Hop Reasoning Framework Over Sparse Knowledge Graph. - Chen Shen; Haizhou Du; Pengfei Li (BESC, 2024)

An Efficient Anomaly Detection Model of Power Consumption Behavior for Industrial Customers. - Jiayu Wang; Yun Chen; Ran Geng; Wenkai Zhao; Zhijun Pan; Chaoran Fu; Xiaohui Wang; Tonghao Chen; Yiwen Cai; Haizhou Du (BESC, 2024)

Context Dynamics Tracking and Curriculum Learning for Emotion Recognition in Conversation. - Feifei Xu; Jiahao Lu; Haizhou Du; Wang Zhou; Ziheng Yu; Tao Sun (BESC, 2024)

FlowSeer: A Novel Framework for Generalized Network Performance Estimation at Flow Level. - Haizhou Du; Ming Li (CSCWD, 2024)

Heracles: A Novel State-based Distributed Verification Framework for DNS Configurations. - Kaiqiang Hu; Haizhou Du; Yao Wang 022 (FMANO@SIGCOMM, 2024)

A Distributed Multi-microgrid Intelligent Scheduling for New Power System. - Xiaohan Guo; Haizhou Du; Weina Zhang (ICPCSEE (1), 2024)

Trafficnet: A Novel Network Performance Prediction Model via Aggregator-Based Enhancement. - Ming Li; Haizhou Du (ICPCSEE (3), 2024)

A Data-Driven Coordinated Active and Reactive Dispatching Strategy for Photovoltaics. - Ye Xu; Haizhou Du (ICPCSEE (3), 2024)

HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links. - Haizhou Du; Yijian Chen; Ryan Yang; Yuchen Li 006; Linghe Kong (NeurIPS, 2024)

FedZipper: A Layer-wise Quantization Compression Framework for Federated Learning with Statistical Heterogeneity. - Haizhou Du; Yan Peng (NPC (2), 2024)

FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios. - Haizhou Du; Zhiyuan Yang (ECML/PKDD (5), 2024)

A unified momentum-based paradigm of decentralized SGD for non-convex models and heterogeneous data. - Haizhou Du; Chaoqian Cheng; Chengdong Ni (Artif. Intell., 2024)

FedSwarm: An Adaptive Federated Learning Framework for Scalable AIoT. - Haizhou Du; Chengdong Ni; Chaoqian Cheng; Qiao Xiang; Xi Chen 009; Xue Liu 001 (IEEE Internet Things J., 2024)

An efficient federated learning framework for graph learning in hyperbolic space. - Haizhou Du; Conghao Liu; Haotian Liu; Xiaoyu Ding; Huan Huo (Knowl. Based Syst., 2024)