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» Transductive Learning from Relational Data
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CCS
2009
ACM
14 years 3 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...
DGO
2010
119views Education» more  DGO 2010»
13 years 10 months ago
Information and transparency: learning from recovery act reporting experiences
The American Recovery and Reinvestment Act (2009) promised strict accounting of all funds spent and the publication of that information to the public in relative real-time. The fe...
Natalie Helbig, Evgeny Styrin, Donna S. Canestraro...
ASUNAM
2010
IEEE
13 years 10 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen
MM
2004
ACM
152views Multimedia» more  MM 2004»
14 years 2 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
AIME
1997
Springer
14 years 26 days ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....