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Effective Acquisition Functions for Active Correlation Clustering
Correlation clustering is a powerful unsupervised learning paradigm that supports positive and negative similarities.
A Unified Active Learning Framework for Annotating Graph Data with Application to Software Source Code Performance Prediction
Then, we convert the tree representation of the source code to a Flow Augmented-AST graph (FA-AST) representation.
Correlation Clustering with Active Learning of Pairwise Similarities
Correlation clustering is a well-known unsupervised learning setting that deals with positive and negative pairwise similarities.
Active Learning of Driving Scenario Trajectories
In this study, we develop a generic active learning framework to annotate driving trajectory time series data.
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