Scalable graph-based semi-supervised learning through sparse Bayesian model

Computer Science

• Semisupervised Learning 100%
• Bayesian Model 100%
• Unlabeled Sample 66%
• Scale Data Set 33%
• Unlabeled Data 33%
• Learning Algorithm 33%
• Generalization Error 16%
• World Application 16%
• Time Complexity 16%
• Learning Framework 16%
• Large Scale Data 16%
• Inference Technique 16%
• Space Complexity 16%