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CORR
2010
Springer

A Unified Algorithmic Framework for Multi-Dimensional Scaling

9 years 10 months ago
A Unified Algorithmic Framework for Multi-Dimensional Scaling
In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is modular; by changing the internals of a single subroutine in the algorithm, we can switch cost functions and target spaces easily. In addition to the formal guarantees of convergence, our algorithms are accurate; in most cases, they converge to better quality solutions than existing methods, in comparable time. We expect that this framework will be useful for a number of MDS variants that have not yet been studied. Categories and Subject Descriptors H.2.8 [Database applications]: Data mining; F.2.2 [Nonnumerical algorithms and problems]: Geometrical algorithms Keywords Multi-dimensional scaling, dimensionality reduction.
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian
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