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106
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NIPS
2008
15 years 1 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby
132
Voted
CORR
2011
Springer
217views Education» more  CORR 2011»
14 years 3 months ago
Coarse-Grained Topology Estimation via Graph Sampling
Many online networks are measured and studied via sampling techniques, which typically collect a relatively small fraction of nodes and their associated edges. Past work in this a...
Maciej Kurant, Minas Gjoka, Yan Wang, Zack W. Almq...
126
Voted
CCECE
2006
IEEE
15 years 5 months ago
New Constraints on Generation of Uniform Random Samples from Evolutionary Trees
In this paper, we introduce new algorithms for selecting taxon samples from large evolutionary trees, maintaining uniformity and randomness, under certain new constraints on the t...
Anupam Bhattacharjee, Zalia Shams, Kazi Zakia Sult...
ECAI
2004
Springer
15 years 5 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
111
Voted
CVPR
2011
IEEE
14 years 7 months ago
Structure from motion for scenes with large duplicate structures
Most existing structure from motion (SFM) approaches for unordered images cannot handle multiple instances of the same structure in the scene. When image pairs containing differen...
Richard Roberts, Sudipta Sinha, Richard Szeliski, ...