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ICML
2009
IEEE
15 years 10 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
PREMI
2005
Springer
15 years 3 months ago
Learning to Segment Document Images
A hierarchical framework for document segmentation is proposed as an optimization problem. The model incorporates the dependencies between various levels of the hierarchy unlike tr...
K. S. Sesh Kumar, Anoop M. Namboodiri, C. V. Jawah...
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CEC
2005
IEEE
14 years 11 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
ICANN
2010
Springer
14 years 11 months ago
Kernel-Based Learning from Infinite Dimensional 2-Way Tensors
Abstract. In this paper we elaborate on a kernel extension to tensorbased data analysis. The proposed ideas find applications in supervised learning problems where input data have ...
Marco Signoretto, Lieven De Lathauwer, Johan A. K....
IEEEICCI
2009
IEEE
14 years 7 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek