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A Robust aCGH Data Recovery Framework Based on Half Quadratic Minimization
This paper presents a general half quadratic framework for simultaneous analysis of the whole array com-
parative genomic hybridization (aCGH) profiles in a data set. The proposed framework accommodates
different ...
A Robust Correntropy-based Method for Analyzing Multisample aCGH Data
This paper presents a new method for analyzing Array comparative genomic hybridization (aCGH) data
based on Correntropy. A new formulation based on low-rank aCGH data and Correntropy is proposed and
its ...
Robust Crowdsourcing-based Linear Regression
In most machine learning problems, the labeling of the training data is an expensive or even impossible task.Crowdsourcing-based learning uses uncertain labels from many non-expert annotators instead of one reference ...
Robust and stable gene selection via Maximum–Minimum Correntropy Criterion
One of the central challenges in cancer research is identifying significant genes among thousands of others on a microarray. Since preventing outbreak and progression of cancer is the ultimate goal in bioinformatics and ...