Online semi-supervised perception: Real-time learning without explicit feedback
The algorithm combines semi-supervised learning on graphs with online learning to enable real-time perception without needing explicit feedback. It builds a graph of data using observed examples and uses offline labeled data as a starting point, refining this graph incrementally with new unlabeled data streams. This allows for adaptive machine learning in scenarios where labeled training data is scarce.