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» Data Clustering Using Evidence Accumulation
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NECO
2008
111views more  NECO 2008»
13 years 7 months ago
A Neural Network Model of the Eriksen Task: Reduction, Analysis, and Data Fitting
We analyze a neural network model of the Eriksen task, a twoalternative forced choice task in which subjects must correctly identify a central stimulus and disregard flankers that...
Yuan Sophie Liu, Philip Holmes, Jonathan D. Cohen
PAMI
2008
197views more  PAMI 2008»
13 years 7 months ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
NIPS
2004
13 years 8 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
11 years 9 months ago
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
PAMI
2006
141views more  PAMI 2006»
13 years 7 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee