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» Combining Multiple Weak Clusterings
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AAAI
2008
13 years 9 months ago
From Comparing Clusterings to Combining Clusterings
This paper presents a fast simulated annealing framework for combining multiple clusterings (i.e. clustering ensemble) based on some measures of agreement between partitions, whic...
Zhiwu Lu, Yuxin Peng, Jianguo Xiao
ICCV
2001
IEEE
14 years 8 months ago
Combining Single View Recognition and Multiple View Stereo for Architectural Scenes
This paper describes a structure from motion and recognition paradigm for generating 3D models from 2D sets of images. In particular we consider the domain of architectural photog...
Anthony R. Dick, Philip H. S. Torr, Simon J. Ruffl...
ICDM
2007
IEEE
170views Data Mining» more  ICDM 2007»
14 years 1 months ago
Consensus Clusterings
In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
Nam Nguyen, Rich Caruana
ECCV
2008
Springer
14 years 8 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
PRIS
2004
13 years 8 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred