Given:
 a set L of labeled training examples
a set U of unlabeled examples

Create a pool U’ of examples by choosing u examples at random from U
Loop for k iterations:
Use L to train a classifier h1 that considers only the x1 portion of x
Use L to train a classifier h2 that considers only the x2 portion of x
Allow h1 to label p positive and n negative examples from U'
Allow h2 to label p positive and n negative examples from U'
Add these self-labeled examples to L
Randomly choose 2p, + 2n examples from U to replenish U'