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OpportunityFinder: A Framework for Automated Causal Inference
We introduce OpportunityFinder, a code-less framework for performing a variety of causal inference studies with panel data for non-expert users.
AutoWS: Automated Weak Supervision Framework for Text Classification
Multiple techniques have been developed to either decrease the dependence of labeled data (zero/few-shot learning, weak supervision) or to improve the efficiency of labeling process (active learning).
Robust Product Classification with Instance-Dependent Noise
Training a product title classification model which is robust to noisy labels in the data is very important to make product classification applications more practical.
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