Generalized Robust Regression for Jointly Sparse Subspace Learning
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2018.2812802
Abstract: Ridge regression is widely used in multiple variable data analysis. However, in very high-dimensional cases such as image feature extraction and recognition, conventional ridge regression or its extensions have the small-class problem, that is, the… read more here.
Keywords: regression; robust regression; generalized robust; subspace learning ... See more keywords
Generalized and Robust Least Squares Regression.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3213594
Abstract: As a simple yet effective method, least squares regression (LSR) is extensively applied for data regression and classification. Combined with sparse representation, LSR can be extended to feature selection (FS) as well, in which l1… read more here.
Keywords: loss function; classification; squares regression; generalized robust ... See more keywords