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Learning with -Graph: -Induced Sparse Subspace Clustering
Yingzhen Yang, Jiashi Feng, Jianchao Yang +1
Sparse subspace clustering methods, such as Sparse Subspace Clustering (SSC) \cite{ElhamifarV13} and -graph \cite{YanW09,ChengYYFH10}, are effective in partitioning the d…
Learning A Task-Specific Deep Architecture For Clustering
Zhangyang Wang, Shiyu Chang, Jiayu Zhou +2
While sparse coding-based clustering methods have shown to be successful, their bottlenecks in both efficiency and scalability limit the practical usage. In recent years, deep lear…
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?
Pooya Khorrami, Tom Le Paine, Thomas S. Huang
Despite being the appearance-based classifier of choice in recent years, relatively few works have examined how much convolutional neural networks (CNNs) can improve performance on…
Learning Deep Encoders
Zhangyang Wang, Qing Ling, Thomas S. Huang
Despite its nonconvex nature, sparse approximation is desirable in many theoretical and application cases. We study the sparse approximation problem with the tool…
DeepFont: Identify Your Font from An Image
Zhangyang Wang, Jianchao Yang, Hailin Jin +4
As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers. We study t…
Deep Networks for Image Super-Resolution with Sparse Prior
Zhaowen Wang, Ding Liu, Jianchao Yang +2
Deep learning techniques have been successfully applied in many areas of computer vision, including low-level image restoration problems. For image super-resolution, several models…