Nonparametric approaches for population structure analysis
L Alhusain, AM Hafez - Human genomics, 2018 - Springer
The analysis of population structure has many applications in medical and population
genetic research. Such analysis is used to provide clear insight into the underlying genetic …
genetic research. Such analysis is used to provide clear insight into the underlying genetic …
Ancestry informative markers for fine-scale individual assignment to worldwide populations
Background and aims The analysis of large-scale genetic data from thousands of individuals
has revealed the fact that subtle population genetic structure can be detected at levels that …
has revealed the fact that subtle population genetic structure can be detected at levels that …
Greedy column subset selection for large-scale data sets
In today's information systems, the availability of massive amounts of data necessitates the
development of fast and accurate algorithms to summarize these data and represent them in …
development of fast and accurate algorithms to summarize these data and represent them in …
Clustered low rank approximation of graphs in information science applications
B Savas, IS Dhillon - Proceedings of the 2011 SIAM International …, 2011 - SIAM
In this paper we present a fast and accurate procedure called clustered low rank matrix
approximation for massive graphs. The procedure involves a fast clustering of the graph and …
approximation for massive graphs. The procedure involves a fast clustering of the graph and …
A Statistical View of Column Subset Selection
We consider the problem of selecting a small subset of representative variables from a large
dataset. In the computer science literature, this dimensionality reduction problem is typically …
dataset. In the computer science literature, this dimensionality reduction problem is typically …
Distributed column subset selection on mapreduce
Given a very large data set distributed over a cluster of several nodes, this paper addresses
the problem of selecting a few data instances that best represent the entire data set. The …
the problem of selecting a few data instances that best represent the entire data set. The …
Clustering-based subset selection in evolutionary multiobjective optimization
Subset selection is an important component in evolutionary multiobjective optimization
(EMO) algorithms. Clustering, as a classic method to group similar data points together, has …
(EMO) algorithms. Clustering, as a classic method to group similar data points together, has …
Data preprocessing impact on machine learning algorithm performance
A Amato, V Di Lecce - Open Computer Science, 2023 - degruyter.com
The popularity of artificial intelligence applications is on the rise, and they are producing
better outcomes in numerous fields of research. However, the effectiveness of these …
better outcomes in numerous fields of research. However, the effectiveness of these …
Spatial random sampling: A structure-preserving data sketching tool
Random column sampling is not guaranteed to yield data sketches that preserve the
underlying structures of the data and may not sample sufficiently from less-populated data …
underlying structures of the data and may not sample sufficiently from less-populated data …
Topics in matrix sampling algorithms
C Boutsidis - arXiv preprint arXiv:1105.0709, 2011 - arxiv.org
We study three fundamental problems of Linear Algebra, lying in the heart of various
Machine Learning applications, namely: 1)" Low-rank Column-based Matrix Approximation" …
Machine Learning applications, namely: 1)" Low-rank Column-based Matrix Approximation" …