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KDD
2010
ACM
195views Data Mining» more  KDD 2010»
13 years 11 months ago
Universal 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 m...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
13 years 11 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
CORR
2011
Springer
161views Education» more  CORR 2011»
13 years 2 months ago
On Parsimonious Explanations for 2-D Tree- and Linearly-Ordered Data
This paper studies the “explanation problem” for tree- and linearly-ordered array data, a problem motivated by database applications and recently solved for the one-dimensiona...
Howard J. Karloff, Flip Korn, Konstantin Makaryche...
BMCBI
2005
101views more  BMCBI 2005»
13 years 7 months ago
MASQOT: a method for cDNA microarray spot quality control
Background: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying ...
Max Bylesjö, Daniel Eriksson, Andreas Sjö...
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
11 years 10 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...