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On Regularization and Inference with Label Constraints
Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured prediction problems.
Learnability with Indirect Supervision Signals
Learning from indirect supervision signals is important in real-world AI applications when, often, gold labels are missing or too costly.
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