Papers with L2 distance loss
Incorporating Priors with Feature Attribution on Text Classification (P19-1)
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| Challenge: | Feature attribution methods are used to help users interpret complex models. |
| Approach: | They propose a feature attribution method that integrates feature attributed features into the objective function to allow machine learning practitioners to incorporate priors in model building. |
| Outcome: | The proposed method reduces undesired model biases without a tradeoff on the original task and improves classifier performance in scarce data setting. |