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* [[Semisupervised learning]] |
* [[Semisupervised learning]] |
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* Multiple-instance learning: "uses training examples grouped into sets, commonly referred to as bags. A single label (either positive or negative) is assigned to each bag. A positive label indicates that the bag includes at least one example belonging to the positive class. A negative label denotes that all instances of the bag belong to the negative class." ([http://link.springer.com/referenceworkentry/10.1007%2F978-0-387-31439-6_308 Torresani, 2016]) |
* Multiple-instance learning: "uses training examples grouped into sets, commonly referred to as bags. A single label (either positive or negative) is assigned to each bag. A positive label indicates that the bag includes at least one example belonging to the positive class. A negative label denotes that all instances of the bag belong to the negative class." ([http://link.springer.com/referenceworkentry/10.1007%2F978-0-387-31439-6_308 Torresani, 2016]) |
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| − | TODO: [http://yoavartzi.com/pub/afz-tutorial.acl.2013.pdf ACL Tutorial 2013 on semantic parsing] |
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| − | What kind of supervision is available? |
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| − | * Annotated parse trees [Miller et al. 1994] |
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| − | * Sentence-LF pairs [Zettlemoyer and Collins 2005] |
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| − | * Question-answer pairs [Clarke et al. 2010] |
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| − | * Instruction-demonstration pairs [Chen and Mooney 2011] |
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| − | * Conversation logs [Artzi and Zettlemoyer 2011] |
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| − | * Visual sensors [Matuszek et al. 2012a] |
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[[Category:Weakly-supervised learning]] |
[[Category:Weakly-supervised learning]] |
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