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» Optimizing Feature Sets for Structured Data
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ICPR
2000
IEEE
15 years 2 months ago
Constrained Mixture Modeling of Intrinsically Low-Dimensional Distributions
In this paper we introduce a novel way of modeling distributions with a low latent dimensionality. Our method allows for a strict control of the properties of the mapping between ...
Joris Portegies Zwart, Ben J. A. Kröse
ICTAI
2010
IEEE
14 years 7 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
SDM
2007
SIAM
167views Data Mining» more  SDM 2007»
14 years 11 months ago
Bandits for Taxonomies: A Model-based Approach
We consider a novel problem of learning an optimal matching, in an online fashion, between two feature spaces that are organized as taxonomies. We formulate this as a multi-armed ...
Sandeep Pandey, Deepak Agarwal, Deepayan Chakrabar...
EUROGP
1999
Springer
166views Optimization» more  EUROGP 1999»
15 years 2 months ago
Adapting the Fitness Function in GP for Data Mining
In this paper we describe how the Stepwise Adaptation of Weights (saw) technique can be applied in genetic programming. The saw-ing mechanism has been originally developed for and ...
Jeroen Eggermont, A. E. Eiben, Jano I. van Hemert
ICML
2009
IEEE
15 years 10 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas