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• W2895230854 abstract "We introduce a new model for online ranking in which the click probability factors into an examination and attractiveness function and the attractiveness function is a linear function of a feature vector and an unknown parameter. Only relatively mild assumptions are made on the examination function. A novel algorithm for this setup is analysed, showing that the dependence on the number of items is replaced by a dependence on the dimension, allowing the new algorithm to handle a large number of items. When reduced to the orthogonal case, the regret of the algorithm improves on the state-of-the-art." @default.
• W2895230854 created "2018-10-12" @default.
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• W2895230854 date "2018-10-05" @default.
• W2895230854 modified "2023-10-05" @default.
• W2895230854 title "Online Learning to Rank with Features" @default.
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• W2895230854 hasPublicationYear "2018" @default.
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