Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically
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Summary
This paper encompasses two complementary dimensions of smoothness: its pointwise nature and probabilistic modeling in a novel framework of Probabilistic Graph-based Pointwise Smoothness (PGP), building upon two foundational models of data closeness and label coupling.
- Type
- article
- Published
- 2014-06-21
- Cited by
- 17
- References
- 35
- OpenAlex
- https://openalex.org/W42041300
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8556751
Keywords
Pointwise, Probabilistic logic, Graph, Computer science, Smoothness
References
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- Learning with Partially Absorbing Random Walks
- Towards rich query interpretation: walking back and forth for mining query templates
- Sensitivity of finite Markov chains under perturbation
- Transductive Inference for Text Classification using Support Vector Machines
- A Primer on Pseudorandom Generators
- Statistical Analysis of Semi-Supervised Regression
- Transductive Learning via Spectral Graph Partitioning
- Unlabeled data: Now it helps, now it doesn't
- Partially labeled classification with Markov random walks
- Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions
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- Walking forward and backward: towards graph-based searching and mining
- Semi-supervised classification in stratified spaces by considering non-interior points using Laplacian behavior
- Towards Context-aware Social Recommendation via Individual Trust
- Enhancing label inference algorithms considering vertex importance in graph-based semi-supervised learning
- Bi-directional Joint Inference for User Links and Attributes on Large Social Graphs
- Robust graph transduction
- Relationship Profiling over Social Networks: Reverse Smoothness from Similarity to Closeness
- Constrained graph-based semi-supervised learning with higher order regularization
- A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification
- Teaching Semi-Supervised Classifier via Generalized Distillation
- Semi-supervised Learning Meets Factorization
- Laplacian Welsch Regularization for Robust Semisupervised Learning
- Pointwise manifold regularization for semi-supervised learning
- Multi-label Topic Classification of Patient Generated Content in a Breast-cancer Community Forum
- Meta-Inductive Node Classification across Graphs
- A Fast Training Method for Transductive Support Vector Machine in Semi-supervised Learning
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