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ISCI
2007
130views more  ISCI 2007»
15 years 6 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
MICCAI
2010
Springer
15 years 5 months ago
Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
ICCAD
2004
IEEE
88views Hardware» more  ICCAD 2004»
16 years 3 months ago
Interconnect lifetime prediction under dynamic stress for reliability-aware design
Thermal effects are becoming a limiting factor in highperformance circuit design due to the strong temperaturedependence of leakage power, circuit performance, IC package cost and...
Zhijian Lu, Wei Huang, John Lach, Mircea R. Stan, ...
GPEM
2008
128views more  GPEM 2008»
15 years 6 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
CVPR
2009
IEEE
17 years 1 months ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof