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» An Abstract Weighting Framework for Clustering Algorithms
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PAMI
2012
11 years 10 months ago
Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers
Abstract—We propose a robust fitting framework, called Adaptive Kernel-Scale Weighted Hypotheses (AKSWH), to segment multiplestructure data even in the presence of a large number...
Hanzi Wang, Tat-Jun Chin, David Suter
APPROX
2007
Springer
67views Algorithms» more  APPROX 2007»
14 years 1 months ago
Maximum Gradient Embeddings and Monotone Clustering
abstract Manor Mendel1 and Assaf Naor2 1 The Open University of Israel 2 Courant Institute Let (X, dX ) be an n-point metric space. We show that there exists a distribution D over ...
Manor Mendel, Assaf Naor
ATAL
2007
Springer
14 years 1 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
14 years 9 months ago
A General Framework for Fast Co-clustering on Large Datasets Using Matrix Decomposition
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
Feng Pan, Xiang Zhang, Wei Wang 0010
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin