Research map / Label-efficient and robust learning / Recognition and long-tail
Active Sampling for Text Classification with Subinstance Level Queries
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Select batches jointly with subinstance sizes using uncertainty, oracle labeling probability, cost, and diversity | Proposed method · Hotel Reviews, IMDB, SRAA, Review Polarity, Sentence Polarity, Wikipedia Movie Plots | test accuracy | Helped |
| Choose batch queries and subinstance sizes rather than query one sample per iteration | Active learning for text classification · Hotel Reviews, IMDB, SRAA, Review Polarity, Sentence Polarity, Wikipedia Movie Plots | test accuracy | Helped |
| Use the proposed subinstance-query framework instead of querying complete samples | BatchRank comparison · Hotel Reviews, IMDB, SRAA, Review Polarity, Sentence Polarity, Wikipedia Movie Plots | test accuracy | Helped |
| Vary subinstance granularity across G1, G2, G3, and G4 (ablation) | Proposed method · IMDB | test accuracy | No clear effect |
| Vary the query budget across 25, 40, 50, 75, 90, and 100 (ablation) | Proposed method · IMDB | test accuracy | No clear effect |
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