Difference between revisions of "Active learning"
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Zeno Gantner (talk | contribs) (Created page with "'''Active learning''' is a learning task where the learner actively selects the instances for which it wants to know the target values. In the context of recommender systems,...") |
Zeno Gantner (talk | contribs) (add paper about active learning and recsys) |
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'''Active learning''' is a learning task where the learner actively selects the instances for which it wants to know the target values. | '''Active learning''' is a learning task where the learner actively selects the instances for which it wants to know the target values. | ||
In the context of [[recommender systems]], an example would be the selection of a list of [[items]] that a [[user]] should rate in order to get improved recommendations. | In the context of [[recommender systems]], an example would be the selection of a list of [[items]] that a [[user]] should rate in order to get improved recommendations. | ||
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| + | == Publication list == | ||
| + | * [http://domino.research.ibm.com/comm/research_people.nsf/pages/rish.index.html I. Rish] and G. Tesauro. ''[http://domino.research.ibm.com/comm/research_people.nsf/pages/rish.index.html/$FILE/ita07_Rish.pdf Active Collaborative Prediction with Maximum Margin Matrix Factorization]'', invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2007. | ||
== External links == | == External links == | ||
Revision as of 10:41, 20 June 2011
Active learning is a learning task where the learner actively selects the instances for which it wants to know the target values. In the context of recommender systems, an example would be the selection of a list of items that a user should rate in order to get improved recommendations.
Publication list
- I. Rish and G. Tesauro. Active Collaborative Prediction with Maximum Margin Matrix Factorization, invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2007.
