Yifei Ding

According to our database, Yifei Ding authored at least 27 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Unsupervised Fault Detection With Deep One-Class Classification and Manifold Distribution Alignment.

Yifei Ding, Minping Jia, Yudong Cao, Xiaoan Yan, Xiaoli Zhao, Chi-Guhn Lee

IEEE Trans. Ind. Informatics, February, 2024

Deep temporal-spectral domain adaptation for bearing fault diagnosis.

Yifei Ding, Yudong Cao, Minping Jia, Peng Ding, Xiaoli Zhao, Chi-Guhn Lee

Knowl. Based Syst., 2024

SegLD: Achieving universal, zero-shot and open-vocabulary segmentation through multimodal fusion via latent diffusion processes.

Hongtao Zheng, Yifei Ding, Zilong Wang, Xinyan Huang

Inf. Fusion, 2024

An autoregressive model-based degradation trend prognosis considering health indicators with multiscale attention information.

Jichao Zhuang, Yudong Cao, Yifei Ding, Minping Jia, Ke Feng

Eng. Appl. Artif. Intell., 2024

2023

Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network.

Xiaoli Zhao, Jianyong Yao, Wenxiang Deng, Peng Ding, Yifei Ding, Minping Jia, Zheng Liu

IEEE Trans. Neural Networks Learn. Syst., September, 2023

Incremental Learning for Remaining Useful Life Prediction via Temporal Cascade Broad Learning System With Newly Acquired Data.

Yudong Cao, Minping Jia, Peng Ding, Xiaoli Zhao, Yifei Ding

IEEE Trans. Ind. Informatics, April, 2023

Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions.

Yifei Ding, Minping Jia, Jichao Zhuang, Yudong Cao, Xiaoli Zhao, Chi-Guhn Lee

Reliab. Eng. Syst. Saf., 2023

Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions.

Yifei Ding, Minping Jia, Yudong Cao, Peng Ding, Xiaoli Zhao, Chi-Guhn Lee

Knowl. Based Syst., 2023

2022

Multiobjective Evolution Enhanced Collaborative Health Monitoring and Prognostics: A Case Study of Bearing Life Test With Three-Axis Acceleration Signals.

Peng Ding, Minping Jia, Jichao Zhuang, Yifei Ding, Yudong Cao, Xiaoli Zhao, Chi-Guhn Lee

IEEE Trans. Instrum. Meas., 2022

Convolutional Transformer: An Enhanced Attention Mechanism Architecture for Remaining Useful Life Estimation of Bearings.

Yifei Ding, Minping Jia

IEEE Trans. Instrum. Meas., 2022

Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings.

Yifei Ding, Jichao Zhuang, Peng Ding, Minping Jia

Reliab. Eng. Syst. Saf., 2022

Deep imbalanced regression using cost-sensitive learning and deep feature transfer for bearing remaining useful life estimation.

Yifei Ding, Minping Jia, Jichao Zhuang, Peng Ding

Appl. Soft Comput., 2022

Intelligent machinery health prognostics under variable operation conditions with limited and variable-length data.

Peng Ding, Minping Jia, Yifei Ding, Yudong Cao, Xiaoli Zhao

Adv. Eng. Informatics, 2022

2021

Statistical Alignment-Based Metagated Recurrent Unit for Cross-Domain Machinery Degradation Trend Prognostics Using Limited Data.

Peng Ding, Minping Jia, Yifei Ding, Xiaoli Zhao

IEEE Trans. Instrum. Meas., 2021

Remaining Useful Life Estimation Under Multiple Operating Conditions via Deep Subdomain Adaptation.

Yifei Ding, Minping Jia, Yudong Cao

IEEE Trans. Instrum. Meas., 2021

A Novel Remaining Useful Life Prediction Method of Rolling Bearings Based on Deep Transfer Auto-Encoder.

Yifei Ding, Peng Ding, Minping Jia

IEEE Trans. Instrum. Meas., 2021

Temporal convolution-based transferable cross-domain adaptation approach for remaining useful life estimation under variable failure behaviors.

Jichao Zhuang, Minping Jia, Yifei Ding, Peng Ding

Reliab. Eng. Syst. Saf., 2021

Remaining useful life estimation using deep metric transfer learning for kernel regression.

Yifei Ding, Minping Jia, Qiuhua Miao, Peng Huang

Reliab. Eng. Syst. Saf., 2021

A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings.

Yudong Cao, Yifei Ding, Minping Jia, Rushuai Tian

Reliab. Eng. Syst. Saf., 2021

A novel Time-frequency Transformer and its Application in Fault Diagnosis of Rolling Bearings.

Yifei Ding, Minping Jia, Qiuhua Miao, Yudong Cao

CoRR, 2021

A High-Availability K-modes Clustering Method Based on Differential Privacy.

Shaobo Zhang, Liujie Yuan, Yuxing Li, Wenli Chen, Yifei Ding

Proceedings of the Algorithms and Architectures for Parallel Processing, 2021

2019

Correction to: Domain agnostic online semantic segmentation for multi-dimensional time series.

Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh

Data Min. Knowl. Discov., 2019

Domain agnostic online semantic segmentation for multi-dimensional time series.

Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh

Data Min. Knowl. Discov., 2019

2018

Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile.

Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh

Data Min. Knowl. Discov., 2018

2017

Query Suggestion to allow Intuitive Interactive Search in Multidimensional Time Series.

Yifei Ding, Eamonn J. Keogh

Proceedings of the 29th International Conference on Scientific and Statistical Database Management, 2017

Matrix Profile VIII: Domain Agnostic Online Semantic Segmentation at Superhuman Performance Levels.

Shaghayegh Gharghabi, Yifei Ding, Chin-Chia Michael Yeh, Kaveh Kamgar, Liudmila Ulanova, Eamonn J. Keogh

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets.

Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh

Proceedings of the IEEE 16th International Conference on Data Mining, 2016