Subspace Learning Based on Tensor Analysis

By Deng Cai, Xiaofei He, Jiawei Han. 2005

64 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Deng Cai
2. Dat Thanh Tran
3. Jiawei Han
4. Xiaofei He
5. Thomas S. Huang
6. Feiping Nie
7. Qun Li
8. Martin Magris

Citations in the corpus

• Tensor representation in high-frequency financial data for price change prediction (2017, methodology): “With advances in mathematical tools and algorithms dealing with tensor input, many multilinear discriminant techniques as well as tensor regression have been proposed for image and video classification problems such as [18], [19], [20], [21], [22], [23], [24], [25], [26], [27].”
• Multilinear Discriminant Analysis for Higher-Order Tensor Data Classification (2014, methodology): “Index Terms—Linear discriminant analysis (LDA), multilinear discriminant analysis (MDA), direct general tensor discriminant analysis (DGTDA), constrained multilinear discriminant analysis (CMDA), pattern classification, higher-order tensor Ç”
• Learning a Spatially Smooth Subspace for Face Recognition (2007, methodology): “Recently there have been a lot of interest in extending the ordinary vector-based subspace learning approaches to tensor space [5, 7, 13, 26, 27].”