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CVPR
2008
IEEE
14 years 9 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ALT
2006
Springer
14 years 4 months ago
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
Hsuan-Tien Lin, Ling Li
ALT
2010
Springer
13 years 9 months ago
Distribution-Dependent PAC-Bayes Priors
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
Guy Lever, François Laviolette, John Shawe-...
FOCS
2008
IEEE
14 years 2 months ago
Learning Geometric Concepts via Gaussian Surface Area
We study the learnability of sets in Rn under the Gaussian distribution, taking Gaussian surface area as the “complexity measure” of the sets being learned. Let CS denote the ...
Adam R. Klivans, Ryan O'Donnell, Rocco A. Servedio
BIOADIT
2004
Springer
13 years 11 months ago
An Artificial Immune System Approach to Misbehavior Detection in Mobile Ad Hoc Networks
Abstract. In mobile ad-hoc networks, nodes act both as terminals and information relays, and participate in a common routing protocol, such as Dynamic Source Routing (DSR). The net...
Jean-Yves Le Boudec, Slavisa Sarafijanovic