Zhiyu Liang

Orcid: 0000-0003-0083-2547

According to our database1, Zhiyu Liang authored at least 26 papers between 2013 and 2024.

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

Timeline

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2024
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Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
FedST: secure federated shapelet transformation for time series classification.
VLDB J., September, 2024

TimeCSL: Unsupervised Contrastive Learning of General Shapelets for Explorable Time Series Analysis.
Proc. VLDB Endow., August, 2024

TodyNet: Temporal dynamic graph neural network for multivariate time series classification.
Inf. Sci., 2024

UniTS: A Universal Time Series Analysis Framework Powered by Self-Supervised Representation Learning.
Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Towards Real-Time Data Ingestion for Industrial Internet of Things.
Proceedings of the Database Systems for Advanced Applications, 2024

iMonitor: A Real-Time Monitoring Platform for Industrial Internet of Things.
Proceedings of the Database Systems for Advanced Applications, 2024

Cnos-Connector: Enabling Seamless Connection with CnosDB to Facilitate Large-Scale Time-Series Data Management and Analytics.
Proceedings of the Database Systems for Advanced Applications, 2024

2023
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation Learning.
Proc. VLDB Endow., November, 2023

The Geometry of Nonlinear Embeddings in Kernel Discriminant Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Unsupervised Multi-modal Feature Alignment for Time Series Representation Learning.
CoRR, 2023

Contrastive Shapelet Learning for Unsupervised Multivariate Time Series Representation Learning.
CoRR, 2023

TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification.
CoRR, 2023

UniTS: A Universal Time Series Analysis Framework with Self-supervised Representation Learning.
CoRR, 2023

FedST: Federated Shapelet Transformation for Interpretable Time Series Classification.
CoRR, 2023

TSC-AutoML: Meta-learning for Automatic Time Series Classification Algorithm Selection.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022
FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification.
Proc. VLDB Endow., 2022

2021
Efficient class-specific shapelets learning for interpretable time series classification.
Inf. Sci., 2021

2020
GMDA: An Automatic Data Analysis System for Industrial Production.
Proceedings of the Database Systems for Advanced Applications, 2020

STRATEGY: A Flexible Job-Shop Scheduling System for Large-Scale Complex Products.
Proceedings of the Database Systems for Advanced Applications, 2020

2019
Low-Power Computer Vision: Status, Challenges, and Opportunities.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019

Low-Power Computer Vision: Status, Challenges, Opportunities.
CoRR, 2019

Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution.
CoRR, 2019

IMOptimizer: An Online Interactive Parameter Optimization System Based on Big Data.
Proceedings of the Database Systems for Advanced Applications, 2019

2018
2018 Low-Power Image Recognition Challenge.
CoRR, 2018

2013
Eigen-analysis of nonlinear PCA with polynomial kernels.
Stat. Anal. Data Min., 2013


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