Semi-supervised learning using Gaussian fields and harmonic functions
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- Type
- article
- Published
- 2003-08-21
- Cited by
- 3,392
- References
- 21
- OpenAlex
- https://openalex.org/W2139823104
Keywords
Artificial intelligence, Gaussian, Semi-supervised learning, Pattern recognition (psychology), Belief propagation
References
- A Random Walks View of Spectral Segmentation
- Link Analysis, Eigenvectors and Stability
- Diffusion Kernels on Graphs and Other Discrete Input Spaces
- Learning from Labeled and Unlabeled Data using Graph Mincuts
- Large Margin Classification Using the Perceptron Algorithm
- Discrete Green's Functions
- Editorial: On Machine Learning
- Grouping with Bias
- A Database for Handwritten Text Recognition Research
- Cluster Kernels for Semi-Supervised Learning
- Partially labeled classification with Markov random walks
- Handwritten Digit Recognition with a Back-Propagation Network
- Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology
- On Spectral Clustering: Analysis and an algorithm
- PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
- Using manifold structure for partially labelled classification
- A Distributed-Cooperative Learning Algorithm for Multi-Layered Neural Networks using a PC Cluster
- Random Walks and Electric Networks
- Normalized cuts and image segmentation
- Fast approximate energy minimization via graph cuts
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- A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI)
- Feature-based transfer learning with real-world applications
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- Antiviral Drug- and Multidrug Resistance in Cytomegalovirus Infected SCT Patients
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- Extensions of Gaussian processes for ranking: semi-supervised and active learning
- Detecting and Preventing Error Propagation via Competitive Learning
- Local Relevance Weighted Maximum Margin Criterion for Text Classification
- A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery
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