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Learning from Partially Annotated Sequences
Published on Nov 30, 20112651 Views
We study sequential prediction models in cases where only fragments of the sequences are annotated with the ground-truth. The task does not match the standard semi-supervised setting and is highly rel
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Chapter list
Protein Secondary Structure Prediction00:00
Part-of-Speech Tagging00:24
Named Entity Recognition01:16
Representation01:40
Structural Perceptrons03:11
Viterbi Algorithm (only transitions) - 104:22
Viterbi Algorithm (only transitions) - 204:44
Labeled Data is Scarce05:25
Research Question06:58
A Simple Transductive Perceptron07:48
Constrained Viterbi Algorithm - 109:08
Constrained Viterbi Algorithm - 209:23
Transductive Loss-augmented Perceptron09:42
Experiments10:22
Varying % of labeled tokens11:30
Adding Partially Labeled Ex.12:17
Automatically + Partially Labeled Data12:51
Wikipedia Corpus - 114:19
Wikipedia Corpus - 214:31
Wikipedia Corpus - 314:39
Wikipedia Corpus - 414:51
Wikipedia Corpus - 515:13
Wikipedia Corpus - 615:16
Characteristics (English)16:03
Mono-lingual Experiment17:06
Cross-lingual NER18:15
Cross-lingual Label Propagation - 118:59
Cross-lingual Label Propagation - 219:03
Cross-lingual Corpus English → Spanish19:11
Characteristics (Spanish)19:20
Cross-lingual Experiment19:54
Conclusion20:19