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Neural Nets for NLP 2021 - Structured Prediction with Local Independence Assumptions
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- 1 CS11-747 Neural Networks for NLP
- 2 A Prediction Problem
- 3 Types of Prediction
- 4 Why Call it "Structured" Prediction?
- 5 Many Varieties of Structured Prediction!
- 6 Why Model Interactions in Output? . Consistency is important! time flies like an arrow
- 7 Sequence Labeling w
- 8 Recurrent Decoder
- 9 Teacher Forcing and Exposure Bias
- 10 An Example of Exposure Bias
- 11 Models w/ Local Dependencies
- 12 Local Normalization vs. Global Normalization
- 13 Conditional Random Fields
- 14 Potential Functions
- 15 BILSTM-CRF for Sequence Labeling
- 16 CRF Training & Decoding
- 17 Forward Calculation Middle Parts
- 18 Forward Calculation: Final Part • Finish up the sentence with the sentence final symbol
- 19 Revisiting the Partition Function
- 20 Training Details
- 21 Generalized Dynamic Programming Models • Decomposition Structure: What structure to use, and thus also what dynamic programming to perform? . Featurization: How do we calculate local scores?
