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» Learning Models for Predicting Recognition Performance
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ICML
2003
IEEE
16 years 7 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
BMCBI
2008
155views more  BMCBI 2008»
15 years 6 months ago
Prediction of regulatory elements in mammalian genomes using chromatin signatures
Background: Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, pro...
Kyoung-Jae Won, Iouri Chepelev, Bing Ren, Wei Wang
ICCV
2007
IEEE
16 years 8 months ago
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
IWCLS
2007
Springer
16 years 23 days ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
ECAL
2007
Springer
16 years 24 days ago
Grounding Action-Selection in Event-Based Anticipation
Anticipation is one of the key aspects involved in flexible and adaptive behavior. The ability for an autonomous agent to extract a relevant model of its coupling with the environ...
Philippe Capdepuy, Daniel Polani, Chrystopher L. N...