Tong Liu

Orcid: 0000-0001-6449-0625

Affiliations:
  • University of Sheffield, OAK Group, Department of Computer Science, UK
  • Chongqing University, School of Automation, Key Laboratory of Dependable Service Computing in Cyber Physical Society, Chongqing, China (PhD 2021)
  • University of Southampton, School of Electronics and Computer Science, Southampton, UK (2018-2019)


According to our database1, Tong Liu authored at least 32 papers between 2016 and 2024.

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

Timeline

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Bibliography

2024
Integrating Visualised Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction.
IEEE Trans. Knowl. Data Eng., October, 2024

Unsupervised Transfer Aided Lifelong Regression for Learning New Tasks Without Target Output.
IEEE Trans. Knowl. Data Eng., September, 2024

Soft Sensor Modeling Based on Vector- Quantized Weighted-Wasserstein VAE for Polyester Polymerization Process.
IEEE Trans. Ind. Informatics, September, 2024

Leak Detection for Natural Gas Gathering Pipelines Under Multiple Operating Conditions Using RP-1dConvLSTM-AE and Multimodel Decision.
IEEE Trans. Ind. Electron., June, 2024

Lifelong Learning Meets Dynamic Processes: An Emerging Streaming Process Prediction Framework With Delayed Process Output Measurement.
IEEE Trans. Control. Syst. Technol., March, 2024

PI-CoF: A Bilevel Optimization Framework for Solving Active Learning Problems using Physics-Information.
Proceedings of the IEEE Conference on Control Technology and Applications, 2024

2023
Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression.
IEEE Trans. Cybern., December, 2023

Corrigendum to 'Sustainable fertilisation management via tensor multi-task learning using multi-dimensional agricultural data': [Journal of Industrial Informatic Integration, Vol 34, August (2023) start page-end page].
J. Ind. Inf. Integr., October, 2023

Efficient multi-task learning with adaptive temporal structure for progression prediction.
Neural Comput. Appl., August, 2023

Sustainable fertilisation management via tensor multi-task learning using multi-dimensional agricultural data.
J. Ind. Inf. Integr., August, 2023

Deep Cascade Gradient RBF Networks With Output-Relevant Feature Extraction and Adaptation for Nonlinear and Nonstationary Processes.
IEEE Trans. Cybern., 2023

Adaptive Real-Time Exploration and Optimization of Safety-Critical Industrial Systems with Ensemble Learning.
Proceedings of the 21st IEEE International Conference on Industrial Informatics, 2023

Weak Regression Enhanced Lifelong Learning for Improved Performance and Reduced Training Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Integrating Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Spatio-Temporal Similarity Measure based Multi-Task Learning for Predicting Alzheimer's Disease Progression using MRI Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Robust Temporal Smoothness in Multi-Task Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Multi-Output Selective Ensemble Identification of Nonlinear and Nonstationary Industrial Processes.
IEEE Trans. Neural Networks Learn. Syst., 2022

Spatio-temporal Tensor Multi-Task Learning for Precision Fertilisation with Real-world Agricultural Data.
Proceedings of the IECON 2022, 2022

Spatio-temporal Tensor Multi-Task Learning for Predicting Alzheimer's Disease in a Longitudinal study.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Multi-task Learning with Adaptive Global Temporal Structure for Predicting Alzheimer's Disease Progression.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2020
Fast Adaptive Gradient RBF Networks For Online Learning of Nonstationary Time Series.
IEEE Trans. Signal Process., 2020

Data-Based Online Optimal Temperature Tracking Control in Continuous Microwave Heating System by Adaptive Dynamic Programming.
Neural Process. Lett., 2020

Integrated CS optimization and OLS for recurrent neural network in modeling microwave thermal process.
Neural Comput. Appl., 2020

Accurate WiFi-based indoor localization by using fuzzy classifier and mlps ensemble in complex environment.
J. Frankl. Inst., 2020

Selective ensemble of multiple local model learning for nonlinear and nonstationary systems.
Neurocomputing, 2020

Growing and Pruning Selective Ensemble Regression for Nonlinear and Nonstationary Systems.
IEEE Access, 2020

2019
Two-Stage Method for Diagonal Recurrent Neural Network Identification of a High-Power Continuous Microwave Heating System.
Neural Process. Lett., 2019

A Multiple Local Model Learning for Nonlinear and Time-Varying Microwave Heating Process.
Proceedings of the International Joint Conference on Neural Networks, 2019

Expert Control System based Hierarchical Control Strategy for Tunnel Microwave Rice Drying.
Proceedings of the 17th European Control Conference, 2019

2018
Learning to Detect Local Overheating of the High-Power Microwave Heating Process With Deep Learning.
IEEE Access, 2018

Adaptive Critic Based Optimal Neurocontrol of a Distributed Microwave Heating System Using Diagonal Recurrent Network.
IEEE Access, 2018

2016
Research on Healthy Anomaly Detection Model Based on Deep Learning from Multiple Time-Series Physiological Signals.
Sci. Program., 2016


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