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 Xuelong Li

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Average citations per article9.75
Citation Count39
Publication count4
Publication years2013-2017
Available for download1
Average downloads per article123.00
Downloads (cumulative)123
Downloads (12 Months)123
Downloads (6 Weeks)20
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August 2017 ACM Transactions on Intelligent Systems and Technology (TIST) - Regular Papers and Special Issue: Data-driven Intelligence for Wireless Networking: Volume 9 Issue 1, October 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 20,   Downloads (12 Months): 123,   Downloads (Overall): 123

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Nonnegative matrix factorization (NMF) is one of the most popular data representation methods in the field of computer vision and pattern recognition. High-dimension data are usually assumed to be sampled from the submanifold embedded in the original high-dimension space. To preserve the locality geometric structure of the data, k -nearest ...
Keywords: image clustering, refined-graph, Data representation, least squares regression, nonnegative matrix factorization (NMF)

2
October 2016 Information Sciences: an International Journal: Volume 364 Issue C, October 2016
Publisher: Elsevier Science Inc.
Bibliometrics:
Citation Count: 1

Nonnegative matrix factorization (NMF) has been successfully used in many fields as a low-dimensional representation method. Projective nonnegative matrix factorization (PNMF) is a variant of NMF that was proposed to learn a subspace for feature extraction. However, both original NMF and PNMF are sensitive to noise and are unsuitable for ...
Keywords: Nonnegative matrix factorization, Robust, Graph regularization, Face recognition

3
December 2013 ICCV '13: Proceedings of the 2013 IEEE International Conference on Computer Vision
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 4

Recently, hashing techniques have been widely applied to solve the approximate nearest neighbors search problem in many vision applications. Generally, these hashing approaches generate 2^c buckets, where c is the length of the hash code. A good hashing method should satisfy the following two requirements: 1) mapping the nearby data ...
Keywords: Approximate Nearest Neighbor Search, Hashing

4
September 2013 IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 35 Issue 9, September 2013
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 33

Recovering a large matrix from a small subset of its entries is a challenging problem arising in many real applications, such as image inpainting and recommender systems. Many existing approaches formulate this problem as a general low-rank matrix approximation problem. Since the rank operator is nonconvex and discontinuous, most of ...
Keywords: Optimization,Approximation methods,Minimization,Convergence,Acceleration,Matrix decomposition,Computer vision,accelerated proximal gradient method,Matrix completion,nuclear norm minimization,alternating direction method of multipliers



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