Proceedings

Learning Optimal Subsets with Implicit User Preferences

Yunsong Guo, Carla P. Gomes

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Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1052-1056.

Abstract

We study the problem of learning an optimal subset from a larger ground set of items, where the optimality criterion is defined by an unknown preference function. We model the problem as a discriminative structural learning problem and solve it using a Structural Support Vector Machine (SSVM) that optimizes a set accuracy performance measure representing set similarities. Our approach departs from previous approaches since we do not explicitly learn a pre-defined preference function. Experimental results on both a synthetic problem domain and a real-world face image subset selection problem show that our method significantly outperforms previous learning approaches for such problems.Yunsong Guo, Carla Gomes

Yunsong Guo, and Carla P. Gomes. 2009. Learning Optimal Subsets with Implicit User Preferences. In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09. IJCAI, 1052–1056. https://ijcai.org/proceedings/2009/178
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