455 citations · 515 across the 8 of their papers we have counts for
6 papers · 1 filter
Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
Yubo Hou, Mohamed Ragab, Yucheng Wang +5
Accurate Remaining Useful Life (RUL) prediction without labeled target domain data is a critical challenge, and domain adaptation (DA) has been widely adopted to address it by tran…
Time-Series Representation Learning via Temporal and Contextual Contrasting
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen +4
Learning decent representations from unlabeled time-series data with temporal dynamics is a very challenging task. In this paper, we propose an unsupervised Time-Series representat…
Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction
Mohamed Ragab, Zhenghua Chen, Min Wu +3
Accurate estimation of remaining useful life (RUL) of industrial equipment can enable advanced maintenance schedules, increase equipment availability and reduce operational costs.…
Ultra-Scalable Spectral Clustering and Ensemble Clustering
Dong Huang, Chang-Dong Wang, Jian-Sheng Wu +2
This paper focuses on scalability and robustness of spectral clustering for extremely large-scale datasets with limited resources. Two novel algorithms are proposed, namely, ultra-…
Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities
Dong Huang, Chang-Dong Wang, Hongxing Peng +2
Ensemble clustering has been a popular research topic in data mining and machine learning. Despite its significant progress in recent years, there are still two challenging issues…
Classification and its applications for drug-target interaction identification
Jian-Ping Mei, Chee-Keong Kwoh, Peng Yang +1
Classification is one of the most popular and widely used supervised learning tasks, which categorizes objects into predefined classes based on known knowledge. Classification has…