Weakly Labeled Training Dataset

A Weakly Labeled Training Dataset is a labeled training dataset whose learning record labels are weakly labeled examples (e.g. by a labeling heuristic).

• AKA: Noisy Labeled Training Data, Weakly Labeled Data.
  • …
• Counter-Example(s):
  • a Strongly Labeled Training Dataset.
• See: Distant Learning Algorithm.

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References

2008

• (Talukdar et al., 2008) ⇒ Partha Pratim Talukdar, Joseph Reisinger, Marius Paşca, Deepak Ravichandran, Rahul Bhagat, and Fernando Pereira. (2008). “Weakly-supervised Acquisition of Labeled Class Instances Using Graph Random Walks.” In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2008).
• (Druck et al., 2008) ⇒ Gregory Druck, Gideon Mann, and Andrew McCallum. (2008). “Learning from Labeled Features Using Generalized Expectation Criteria.” In: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2008). doi:10.1145/1390334.1390436

2002

• (Bockhorst et al., 2002) ⇒ Joseph Bockhorst, and Mark Craven. (2002). “Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data.” In: Proceedings of the Nineteenth International Conference on Machine Learning (ICML 2002).

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