The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
The outlier detection problem has important applications in the eld of fraud detection, network robustness analysis, and intrusion detection. Most such applications are high dimen...
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a highdimensional data matrix despite both small entry-wise noise and gross spar...
Zihan Zhou, Xiaodong Li, John Wright, Emmanuel J. ...