Sparse Principal Component Analysis via Variable Projection
نویسندگان
چکیده
منابع مشابه
Sparse Principal Component Analysis via Variable Projection
Sparse principal component analysis (SPCA) has emerged as a powerful technique for modern data analysis. We discuss a robust and scalable algorithm for computing sparse principal component analysis. Specifically, we model SPCA as a matrix factorization problem with orthogonality constraints, and develop specialized optimization algorithms that partially minimize a subset of the variables (varia...
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ژورنال
عنوان ژورنال: SIAM Journal on Applied Mathematics
سال: 2020
ISSN: 0036-1399,1095-712X
DOI: 10.1137/18m1211350