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AAAI
2012
13 years 6 months ago
Discriminative Clustering via Generative Feature Mapping
Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Liwei Wang, Xiong Li, Zhuowen Tu, Jiaya Jia
AAAI
2008
15 years 6 months ago
Concept-Based Feature Generation and Selection for Information Retrieval
Traditional information retrieval systems use query words to identify relevant documents. In difficult retrieval tasks, however, one needs access to a wealth of background knowled...
Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch
PPSN
2010
Springer
15 years 2 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
IBPRIA
2005
Springer
15 years 9 months ago
Gabor Parameter Selection for Local Feature Detection
Abstract. Some recent works have addressed the object recognition problem by representing objects as the composition of independent image parts, where each part is modeled with “...
Plinio Moreno, Alexandre Bernardino, José S...
JMLR
2010
104views more  JMLR 2010»
14 years 11 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic