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» Adaptive importance sampling in general mixture classes
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CVPR
2008
IEEE
16 years 1 months ago
Constrained spectral clustering through affinity propagation
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as ...
Miguel Á. Carreira-Perpiñán, ...
213
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DAGM
2011
Springer
13 years 11 months ago
Agnostic Domain Adaptation
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Alexander Vezhnevets, Joachim M. Buhmann
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 3 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
97
Voted
PR
2008
151views more  PR 2008»
14 years 11 months ago
Constraint Score: A new filter method for feature selection with pairwise constraints
Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to ...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
81
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ATAL
2007
Springer
15 years 5 months ago
Multiagent learning in adaptive dynamic systems
Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...
Andriy Burkov, Brahim Chaib-draa