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Found 5 papers, 2 papers with code
Multi-task manifold learning for small sample size datasets
For instance transfer, datasets are merged among similar tasks, whereas for model transfer, the manifold models are averaged among similar tasks.
Principal component analysis for Gaussian process posteriors
This paper proposes an extension of principal component analysis for Gaussian process (GP) posteriors, denoted by GP-PCA.
Stopping Criterion for Active Learning Based on Error Stability
Active learning is a framework for supervised learning to improve the predictive performance by adaptively annotating a small number of samples.
Visual analytics of set data for knowledge discovery and member selection support
A typical target application is a visual support system for team analysis and member selection, by which users can analyze past teams and examine candidate lineups for new teams.
Stopping criterion for active learning based on deterministic generalization bounds
Active learning is a framework in which the learning machine can select the samples to be used for training.
