Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation

2020 ◽  
Vol 22 (11) ◽  
pp. 2844-2857 ◽  
Author(s):  
Yongshan Zhang ◽  
Jia Wu ◽  
Zhihua Cai ◽  
Philip S. Yu
Keyword(s):  
Feature Selection ◽  
Image Annotation ◽  
Selection For ◽  
Sparse Feature Selection

scholarly journals Machine learning methods in the computational biology of cancer

2014 ◽  
Vol 470 (2167) ◽  
pp. 20140081 ◽  
Author(s):  
M. Vidyasagar
Keyword(s):  
Machine Learning ◽  
Ovarian Cancer ◽  
Feature Selection ◽  
Classification Problems ◽  
Open Problems ◽  
Machine Learning Methods ◽  
Selection For ◽  
Personalized Cancer Therapy ◽  
Personalized Cancer ◽  
Sparse Feature Selection

The objectives of this Perspective paper are to review some recent advances in sparse feature selection for regression and classification, as well as compressed sensing, and to discuss how these might be used to develop tools to advance personalized cancer therapy. As an illustration of the possibilities, a new algorithm for sparse regression is presented and is applied to predict the time to tumour recurrence in ovarian cancer. A new algorithm for sparse feature selection in classification problems is presented, and its validation in endometrial cancer is briefly discussed. Some open problems are also presented.

scholarly journals Sparse feature selection for classification and prediction of metastasis in endometrial cancer

BMC Genomics ◽  
2017 ◽  
Vol 18 (S3) ◽  
Author(s):  
Mehmet Eren Ahsen ◽  
Todd P. Boren ◽  
Nitin K. Singh ◽  
Burook Misganaw ◽  
David G. Mutch ◽  
...  
Keyword(s):  
Feature Selection ◽  
Endometrial Cancer ◽  
Prediction Of Metastasis ◽  
Selection For ◽  
Sparse Feature Selection

Manifold regularized multi-view feature selection for social image annotation

2016 ◽  
Vol 204 ◽  
pp. 135-141 ◽  
Author(s):  
Yangxi Li ◽  
Xin Shi ◽  
Cuilan Du ◽  
Yang Liu ◽  
Yonggang Wen
Keyword(s):  
Feature Selection ◽  
Image Annotation ◽  
Social Image ◽  
Selection For
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