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ICML
2006
IEEE
15 years 10 months ago
MISSL: multiple-instance semi-supervised learning
There has been much work on applying multiple-instance (MI) learning to contentbased image retrieval (CBIR) where the goal is to rank all images in a known repository using a smal...
Rouhollah Rahmani, Sally A. Goldman
ICML
1996
IEEE
15 years 10 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
CVPR
2009
IEEE
16 years 5 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
AAAI
2008
15 years 10 days ago
Semi-Supervised Ensemble Ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Steven C. H. Hoi, Rong Jin
ECML
2003
Springer
15 years 3 months ago
Ensembles of Multi-instance Learners
In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. Through analyzin...
Zhi-Hua Zhou, Min-Ling Zhang