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JMLR
2011

Models of Cooperative Teaching and Learning

11 years 3 months ago
Models of Cooperative Teaching and Learning
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooperative teacher that selects “helpful” training examples. The number of training examples a learner needs for identifying a concept in a given class C of possible target concepts (sample complexity of C) is lower in models assuming such teachers, that is, “helpful” examples can speed up the learning process. The problem of how a teacher and a learner can cooperate in order to reduce the sample complexity, yet without using “coding tricks”, has been widely addressed. Nevertheless, the resulting teaching and learning protocols do not seem to make the teacher select intuitively “helpful” examples. The two models introduced in this paper are built on what we call subset teaching sets and recursive teaching sets. They extend previous models of teaching by letting both the teacher and the learner expl...
Sandra Zilles, Steffen Lange, Robert Holte, Martin
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where JMLR
Authors Sandra Zilles, Steffen Lange, Robert Holte, Martin Zinkevich
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