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MCS
2009
Springer
15 years 10 months ago
A Study of Semi-supervised Generative Ensembles
Machine Learning can be divided into two schools of thought: generative model learning and discriminative model learning. While the MCS community has been focused mainly on the lat...
Manuela Zanda, Gavin Brown
ICML
2005
IEEE
16 years 4 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
138
Voted
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 6 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
WEBI
2009
Springer
15 years 9 months ago
Adapting Reinforcement Learning for Trust: Effective Modeling in Dynamic Environments
—In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about...
Özgür Kafali, Pinar Yolum
PRIMA
2009
Springer
15 years 9 months ago
An Adaptive Agent Model for Emotion Reading by Mirroring Body States and Hebbian Learning
In recent years, the topic of emotion reading has increasingly received attention from researchers in Cognitive Science and Artificial Intelligence. To study this phenomenon, in th...
Tibor Bosse, Zulfiqar A. Memon, Jan Treur