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Displaying 1-4 out of 4 total
Complementary Projection Hashing
2013 IEEE International Conference on Computer Vision (ICCV)
By Zhongming Jin,Yao Hu,Yue Lin,Debing Zhang,Shiding Lin,Deng Cai,Xuelong Li
Issue Date:December 2013
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 me...
Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
By Yao Hu, Debing Zhang, Jieping Ye, Xuelong Li, Xiaofei He
Issue Date:September 2013
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 approxim...
Matrix completion by Truncated Nuclear Norm Regularization
2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
By Debing Zhang, Yao Hu, Jieping Ye, Xuelong Li, Xiaofei He
Issue Date:June 2012
Estimating missing values in visual data is a challenging problem in computer vision, which can be considered as a low rank matrix approximation problem. Most of the recent studies use the nuclear norm as a convex relaxation of the rank operator. However, ...
Accelerated singular value thresholding for matrix completion
Found in: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '12)
By Debing Zhang, Jieping Ye, Jun Liu, Xiaofei He, Yao Hu
Issue Date:August 2012
Recovering a large matrix from a small subset of its entries is a challenging problem arising in many real world applications, such as recommender system and image in-painting. These problems can be formulated as a general matrix completion problem. The Si...
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