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168
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ICML
2003
IEEE
16 years 1 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
IJCNN
2008
IEEE
15 years 7 months ago
A neural wake-sleep learning architecture for associating robotic facial emotions
—A novel wake-sleep learning architecture for processing a robot’s facial expressions is introduced. According to neuroscience evidence, associative learning of emotional respo...
Chi-Yung Yau, Kevin Burn, Stefan Wermter
90
Voted
ICML
2008
IEEE
16 years 1 months ago
Dirichlet component analysis: feature extraction for compositional data
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
Hua-Yan Wang, Qiang Yang, Hong Qin, Hongbin Zha
84
Voted
ICML
2010
IEEE
15 years 1 months ago
Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...
Zeeshan Syed, Ilan Rubinfeld
98
Voted
MLDM
2008
Springer
15 years 17 days ago
Classification Based on Consistent Itemset Rules
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura