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» Synthesizing Learners Tolerating Computable Noisy Data
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CVPR
2004
IEEE
14 years 9 months ago
Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and Its Applications
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Kun Huang, René Vidal, Yi Ma
ICDM
2005
IEEE
179views Data Mining» more  ICDM 2005»
14 years 1 months ago
Bagging with Adaptive Costs
Ensemble methods have proved to be highly effective in improving the performance of base learners under most circumstances. In this paper, we propose a new algorithm that combine...
Yi Zhang, W. Nick Street
PKDD
2001
Springer
127views Data Mining» more  PKDD 2001»
13 years 12 months ago
Sentence Filtering for Information Extraction in Genomics, a Classification Problem
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...
Claire Nedellec, Mohamed Ould Abdel Vetah, Philipp...
ICPR
2006
IEEE
14 years 8 months ago
Shape Alignment by Learning a Landmark-PDM Coupled Model
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the...
Yifeng Jiang, Jun Xie, Hung-Tat Tsui
COGSCI
2010
125views more  COGSCI 2010»
13 years 7 months ago
A Probabilistic Computational Model of Cross-Situational Word Learning
Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...
Afsaneh Fazly, Afra Alishahi, Suzanne Stevenson