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A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
A review of distributed algorithms for principal component analysis
Principal component analysis (PCA) is a fundamental primitive of many data analysis, array
processing, and machine learning methods. In applications where extremely large arrays of …
processing, and machine learning methods. In applications where extremely large arrays of …
Distributed estimation of principal eigenspaces
Principal component analysis (PCA) is fundamental to statistical machine learning. It extracts
latent principal factors that contribute to the most variation of the data. When data are stored …
latent principal factors that contribute to the most variation of the data. When data are stored …
Low rank approximation with entrywise l1-norm error
We study the ℓ1-low rank approximation problem, where for a given nxd matrix A and
approximation factor α≤ 1, the goal is to output a rank-k matrix  for which‖ A-Â‖ 1≤ α …
approximation factor α≤ 1, the goal is to output a rank-k matrix  for which‖ A-Â‖ 1≤ α …
In-network PCA and anomaly detection
We consider the problem of network anomaly detection in large distributed systems. In this
setting, Principal Component Analysis (PCA) has been proposed as a method for discover …
setting, Principal Component Analysis (PCA) has been proposed as a method for discover …
Relative error tensor low rank approximation
We consider relative error low rank approximation of tensors with respect to the Frobenius
norm. Namely, given an order-q tensor A∊ ℝ∏ i= 1 q ni, output a rank-k tensor B for which …
norm. Namely, given an order-q tensor A∊ ℝ∏ i= 1 q ni, output a rank-k tensor B for which …
A survey of emerging trend detection in textual data mining
What is an emerging trend? An emerging trend is a topic area that is growing in interest and
utility over time. For example, Extensible Markup Language (XML) emerged as a trend in the …
utility over time. For example, Extensible Markup Language (XML) emerged as a trend in the …
Optimal principal component analysis in distributed and streaming models
This paper studies the Principal Component Analysis (PCA) problem in the distributed and
streaming models of computation. Given a matrix A∈ R m× n, a rank parameter k< rank (A) …
streaming models of computation. Given a matrix A∈ R m× n, a rank parameter k< rank (A) …
Improved distributed principal component analysis
We study the distributed computing setting in which there are multiple servers, each holding
a set of points, who wish to compute functions on the union of their point sets. A key task in …
a set of points, who wish to compute functions on the union of their point sets. A key task in …