Application areas

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We tackle a wide variety of data-driven applications via investigating optimization and machine learning techniques. Here are some exemplified applications, but we do not restrict ourselves to them.



Low-rank approximation has attracted more and more attention in the community of recommendation. A fundamental assumption in constructing matrix approximations is that the partially observed data matrix is of low-rank.

Movie recomenndation by matrix completion problem.

Video surveillance (anomaly detection)

Video sequence understanding by online subspace learning with matrix and tensor representations.

Image processing (recovery, basis representation, and denoising)

Hyperspectral image recovery on the Ribeira dataset
Basis representations on the CBCL dataset.
Denoising on the COIL20 dataset.

Network traffic analysis (anomaly traffic detection via inverse problem)

Anomaly traffic volume detection by inverse problem.

Wireless system architecture design

Architecture design of hybrid precoder large-scale millimeter wave (mmWave) MIMO systems.

General-purpose data analysis

Principal component analysis (PCA).