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Xiaodong Lin
Researcher at Rutgers University
Publications - 64
Citations - 3060
Xiaodong Lin is an academic researcher from Rutgers University. The author has contributed to research in topics: Computer science & Linearization. The author has an hindex of 19, co-authored 49 publications receiving 2796 citations. Previous affiliations of Xiaodong Lin include Purdue University & National Institutes of Health.
Papers
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Journal ArticleDOI
Tools for privacy preserving distributed data mining
TL;DR: This paper presents some components of a toolkit of components that can be combined for specific privacy-preserving data mining applications, and shows how they can be used to solve several Privacy preserving data mining problems.
Journal ArticleDOI
Gene selection using support vector machines with non-convex penalty
TL;DR: A unified procedure for simultaneous gene selection and cancer classification is provided, achieving high accuracy in both aspects and a successive quadratic algorithm is proposed to convert the non-differentiable and non-convex optimization problem into easily solved linear equation systems.
Proceedings ArticleDOI
Privacy preserving regression modelling via distributed computation
TL;DR: This paper describes an algorithm that enables agencies wanting to conduct a linear regression analysis with complete records without disclosing values of their own attributes to compute the exact regression coefficients of the global regression equation and also perform some basic goodness-of-fit diagnostics while protecting the confidentiality of their data.
Journal ArticleDOI
Privacy-preserving clustering with distributed EM mixture modeling
TL;DR: A technique that uses EM mixture modeling to perform clustering on distributed data that controls data sharing, preventing disclosure of individual data items or any results that can be traced to an individual site.
Journal ArticleDOI
Secure Regression on Distributed Databases
TL;DR: This article presents several methods for performing linear regression on the union of distributed databases that preserve, to varying degrees, confidentiality of those databases.