Papers by Menglin Jia
When in Doubt: Improving Classification Performance with Alternating Normalization (2021.findings-emnlp)
Copied to clipboard
| Challenge: | a classifier that uses a nonparametric post-processing step for classification suffers when given examples that are close to its decision boundary. |
| Approach: | They propose a nonparametric post-processing step that re-adjusts predicted class probability distributions using high-confidence validation examples. |
| Outcome: | The proposed method improves classifier accuracy on difficult examples. |