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FLAIRS
2001
15 years 8 months ago
Multiple Predicate Learning for Document Image Understanding
Documentimageunderstandingdenotesthe recognition of semanticallyrelevant componentsin the layout extracted froma documentimage.This recognitionprocessis based on somevisual models...
Floriana Esposito, Donato Malerba, Francesca A. Li...
NIPS
2004
15 years 8 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
JMLR
2006
97views more  JMLR 2006»
15 years 6 months ago
Learning Coordinate Covariances via Gradients
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
Sayan Mukherjee, Ding-Xuan Zhou
CVPR
2007
IEEE
15 years 10 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
ECML
2006
Springer
15 years 10 months ago
Combinatorial Markov Random Fields
Abstract. A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatoria...
Ron Bekkerman, Mehran Sahami, Erik G. Learned-Mill...