D. Lee, "A systematic review of multi-label feature selection and a new method based on label construction," Neurocomputing, vol. 180, no. C, pp. 3-15, 2016.Newton Spolao藛r, Maria Carolina Monard, Grigorios Tsoumakas, and Huei Diana Lee. A systematic review of multi-label feature ...
摘要: Applied Intelligence - Feature selection for multilabel data is a challenging and meaningful work. The information contained in multilabel data is more abundant, which may help further mine...关键词: Multilabel Feature selection NMF Manifold learning Sparse regularization ...
[11] D. Cai, C. Zhang, and X. He. Unsupervised feature selection for multi-cluster data. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 333-342. ACM, 2010. [12] A.C. Carvalho, R.F. Mello, S. Alelyani, H. Liu, et al...
The AQ Family of Learning Programs: A Review of Recent Developments and an Exemplary Application; Reports of Machine Learning and Inference Laboratory, George Mason University: Fairfax, VA, USA, 1991. [Google Scholar] Wang, J.; Zhang, X. Matrix approaches for some issues about minimal and ...
Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey. arXiv 2023 paper bib Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, Yaowei Wang, Yonghong Tian, Wen Gao On Efficient Training of Large-Scale Deep Learning Models: A Literature Review. arXiv 2023 paper...
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation [TNNLS 2020] Deep Visual Domain Adaptation: A Survey [Neurocomputing 2018] A Survey on Deep Transfer Learning [ICANN2018] Visual domain adaptation: A survey of recent advances [2015] Theory Arxiv A Theory of Label Propagation ...
A review of feature selection methods on synthetic data Knowl. Inf. Syst., 34 (3) (2013), pp. 483-519, 10.1007/s10115-012-0487-8 Google Scholar Caesar et al., 2015 Caesar, H., Uijlings, J.R.R., Ferrari, V., 2015. Joint calibration for semantic segmentation, CoRR abs/1507.01581....
The subsequent phase of the research will encompass an in-depth literature review, offering a comprehensive summary of the pertinent studies conducted in the field. After that, each of the parts of the proposed framework will be explained. The experimental results, which provide convincing proof of...
You can also label documents and train models using the Document Intelligence REST API. To train and Analyze with the REST API, see Train with labels using the REST API and Python. Set up input data First, make sure all the training documents are of the same format. If you have forms ...
Owing to their strong learning and accurate prediction abilities, all sorts of AI models have also been applied in wastewater treatment (WWT) to optimize the process, predict the efficiency and evaluate the performance, so as to explore more cost-effective solutions to WWT. In this review, we ...