Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...
Detection of near duplicate documents is an important problem in many data mining and information filtering applications. When faced with massive quantities of data, traditional d...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
Recent efforts to add new services to the Internet have increased interest in software-based routers that are easy to extend and evolve. This paper describes our experiences using...
Tammo Spalink, Scott Karlin, Larry L. Peterson, Yi...
This paper studies the problem of simultaneously aligning a batch of linearly correlated images despite gross corruption (such as occlusion). Our method seeks an optimal set of im...
Yigang Peng, Arvind Balasubramanian, John Wright, ...
Most existing video denoising algorithms assume a single statistical model of image noise, e.g. additive Gaussian white noise, which often is violated in practice. In this paper, ...