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UNIVERSAL REPRESENTATIONS
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Classroom Contents
Transfer Learning Larochelle
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- 1 Intro
- 2 WHYTRANSFER LEARNING • Deep leaming successes have required a lot of labeled training data
- 3 FEW-SHOT LEARNING
- 4 MODERN TRANSFER LEARNING: FINE-TUNING
- 5 LEARNING PROBLEM STATEMENT
- 6 PROTOTYPICAL NETWORKS
- 7 MODEL-AGNOSTIC META-LEARNING • Training a 'fine-tuning procedure
- 8 EVALUATION: META-DATASET
- 9 UNIVERSAL REPRESENTATIONS
- 10 UNIVERSAL REPRESENTATION TRANSFORMER
- 11 RESULTS
- 12 REMAINING CHALLENGES
