Haizhou Du

Orcid: 0000-0002-1875-5159

According to our database1, Haizhou Du authored at least 53 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
An efficient federated learning framework for graph learning in hyperbolic space.
Knowl. Based Syst., 2024

FedSwarm: An Adaptive Federated Learning Framework for Scalable AIoT.
IEEE Internet Things J., 2024

A unified momentum-based paradigm of decentralized SGD for non-convex models and heterogeneous data.
Artif. Intell., 2024

FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Heracles: A Novel State-based Distributed Verification Framework for DNS Configurations.
Proceedings of the 2024 SIGCOMM Workshop on Formal Methods Aided Network Operation, 2024

FlowSeer: A Novel Framework for Generalized Network Performance Estimation at Flow Level.
Proceedings of the 27th International Conference on Computer Supported Cooperative Work in Design, 2024

Rethinking DNS Configuration Verification with a Distributed Architecture.
Proceedings of the 8th Asia-Pacific Workshop on Networking, 2024

2023
An efficient joint framework for interacting knowledge graph and item recommendation.
Knowl. Inf. Syst., April, 2023

An efficient federated learning framework for multi-channeled mobile edge network with layered gradient compression.
Comput. Networks, February, 2023

Heterogeneous Reinforcement Learning Network for Aspect-Based Sentiment Classification With External Knowledge.
IEEE Trans. Affect. Comput., 2023

A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data.
CoRR, 2023

Toward a Unified Framework for Verifying and Interpreting Learning-Based Networking Systems.
Proceedings of the 31st IEEE/ACM International Symposium on Quality of Service, 2023

What Appears Suboptimal May Surprise You: A Fixed-Rate Scheduling Policy for Geo-Distributed CoFlows.
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

Baileys: An Efficient Distributed Machine Learning Framework by Dynamic Grouping.
Proceedings of the 15th International Conference on Machine Learning and Computing, 2023

2022
Nostradamus: A novel event propagation prediction approach with spatio-temporal characteristics in non-Euclidean space.
Neural Networks, 2022

Isomer: Transfer enhanced dual-channel heterogeneous dependency attention network for aspect-based sentiment classification.
Knowl. Based Syst., 2022

Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions.
CoRR, 2022

Finder: A novel approach of change point detection for multivariate time series.
Appl. Intell., 2022

Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings.
Proceedings of the IEEE Military Communications Conference, 2022

Sailfish: A Fast Bayesian Change Point Detection Framework with Gaussian Process for Time Series.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Orchestra: adaptively accelerating distributed deep learning in heterogeneous environments.
Proceedings of the CF '22: 19th ACM International Conference on Computing Frontiers, Turin, Italy, May 17, 2022

2021
Astrologer: Exploiting graph neural Hawkes process for event propagation prediction with spatio-temporal characteristics.
Knowl. Based Syst., 2021

CPMAN: Change Point Detection Approach in Time Series Based on the Prediction of Multi-stage Attention Networks.
Int. J. Artif. Intell. Tools, 2021

XFinder: Detecting Unknown Anomalies in Distributed Machine Learning Scenario.
Frontiers Comput. Sci., 2021

Isomer: Transfer enhanced Dual-Channel Heterogeneous Dependency Attention Network for Aspect-based Sentiment Classification.
CoRR, 2021

Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning.
CoRR, 2021

Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression.
CoRR, 2021

Stargazer: Toward efficient data analytics scheduling via task completion time inference.
Comput. Electr. Eng., 2021

Symbiosis: A Novel Framework for Integrating Hierarchies from Knowledge Graph into Recommendation System.
Proceedings of the Knowledge Science, Engineering and Management, 2021

FLZip: An Efficient and Privacy-Preserving Framework for Cross-Silo Federated Learning.
Proceedings of the 2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2021

Trident: Change Point Detection for Multivariate Time Series via Dual-Level Attention Learning.
Proceedings of the Intelligent Information and Database Systems - 13th Asian Conference, 2021

2020
MonkeyKing: Adaptive Parameter Tuning on Big Data Platforms with Deep Reinforcement Learning.
Big Data, 2020

Hawkeye: Adaptive Straggler Identification on Heterogeneous Spark Cluster With Reinforcement Learning.
IEEE Access, 2020

Dawn: Co-programming Distributed Applications with Network Control.
Proceedings of the 2020 Workshop on Network Application Integration/CoDesign, 2020

Controllable Multi-Character Psychology-Oriented Story Generation.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
A novel graph compression algorithm for data-intensive scientific networks.
Int. J. High Perform. Comput. Netw., 2019

Hephaistos: A fast and distributed outlier detection approach for big mixed attribute data.
Intell. Data Anal., 2019

OctopusKing: A TCT-Aware Task Scheduling on Spark Platform.
Proceedings of the 25th IEEE International Conference on Parallel and Distributed Systems, 2019

Cheetah: A Dynamic Performance Optimization Approach on Heterogeneous Big Data Analytics Cluster.
Proceedings of the 5th International Conference on Big Data Computing and Communications, 2019

Multi-Stage Mixed Attribute Outlier Detection Algorithm Based on Neighborhood Density Difference.
Proceedings of the 5th International Conference on Big Data Computing and Communications, 2019

2018
Octopus: Based on Congestion-aware Scheduling on Geo-distributed Big Data Analytics Cluster.
Proceedings of the 5th International Conference on Systems and Informatics, 2018

Hierarchical Gated Convolutional Networks with Multi-Head Attention for Text Classification.
Proceedings of the 5th International Conference on Systems and Informatics, 2018

Otterman: A Novel Approach of Spark Auto-tuning by a Hybrid Strategy.
Proceedings of the 5th International Conference on Systems and Informatics, 2018

FASTBEE: A Fast and Self-Adaptive Clustering Algorithm Towards to Edge Computing.
Proceedings of the 5th IEEE International Conference on Cyber Security and Cloud Computing, 2018

MMDBC: Density-Based Clustering Algorithm for Mixed Attributes and Multi-dimension Data.
Proceedings of the 2018 IEEE International Conference on Big Data and Smart Computing, 2018

2016
Robust K-means algorithm with automatically splitting and merging clusters and its applications for surveillance data.
Multim. Tools Appl., 2016

A Novel Text Feature Weight Calculation Method Applied to Power Field.
Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, 2016

Novel clustering-based approach for Local Outlier Detection.
Proceedings of the IEEE Conference on Computer Communications Workshops, 2016

2015
Robust local outlier detection with statistical parameter for big data.
Comput. Syst. Sci. Eng., 2015

Robust Local Outlier Detection.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2012
A fuzzy clustering algorithm based on interval valued fuzzy sets.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012

2011
Study of a Fuzzy Clustering Algorithm Based on Interval Value.
Proceedings of the Web Information Systems and Mining - International Conference, 2011

An Efficient Fuzzy Rough Approach for Feature Selection.
Proceedings of the Rough Sets and Knowledge Technology - 6th International Conference, 2011


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