semi-supervising
self-learning
逐次迭代,
Repeat:
- train model f*from labelled set
- Apply f*to the unlabeled date set.(get Pseudo-label)
- add a set of unlabeled data to labelled data。jump to 1.
Hard Label V.S. Soft Label
极大似然估计(Maxmize likelihood)
Entropy-based Regularization
没太听懂
Semi-SVM
Smoothness Assumption
x1与x2之间有high density region
example:
Cluster(簇) and then Label
Graph-based Approach
K Nearest Neighbor