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CORR
2006
Springer
109views Education» more  CORR 2006»
14 years 11 months ago
Decision Making with Side Information and Unbounded Loss Functions
We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly differe...
Majid Fozunbal, Ton Kalker
100
Voted
TSMC
2008
122views more  TSMC 2008»
14 years 11 months ago
A Geometric Approach to the Theory of Evidence
In this paper, we propose a geometric approach to the theory of evidence based on convex geometric interpretations of its two key notions of belief function (b.f.) and Dempster...
Fabio Cuzzolin
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
14 years 9 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
88
Voted
ICASSP
2011
IEEE
14 years 2 months ago
Optimization of the antenna array geometry based on a Bayesian DOA estimation criterion
In this paper, we address the problem of the sensor placement for estimating the direction of a narrow-band source, randomly located in the far-field of a planar antenna array. E...
Houcem Gazzah, Jean Pierre Delmas
ICML
2007
IEEE
15 years 12 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore