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ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
15 years 10 months ago
Error-Aware Density-Based Clustering of Imprecise Measurement Values
Manufacturing process development is under constant pressure to achieve a good yield for stable processes. The development of new technologies, especially in the field of photoma...
Dirk Habich, Peter Benjamin Volk, Wolfgang Lehner,...
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 9 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
ITSL
2008
15 years 5 months ago
An Empirical Comparison of NML Clustering Algorithms
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Petri Kontkanen, Petri Myllymäki
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICMCS
2006
IEEE
94views Multimedia» more  ICMCS 2006»
15 years 10 months ago
Semantic Labeling of Multimedia Content Clusters
In this paper we present a novel approach for labeling clusters of multimedia content that leverages supervised classification techniques in conjunction with unsupervised cluster...
Jelena Tesic, John R. Smith