Algorithm 1.
Progressive Semi-supervised Learning
| Input: θ, L, U | |
| Output: updated θ | |
| 1: | while len(U) > 0 do |
| 2: | Estimate SU by θ |
| 3: | Move k best pairs (IU, SU) from U to L |
| 4: | Optimize θ by training on L |
| 5: | return θ |
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