Universal Approximation Functions for Fast Learning to Rank

international acm sigir conference on research and development in information retrieval, pp. 1017-1020, 2018.

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Learning to rank is a key component of modern information retrieval systems. Recently, regression forest models (i.e., random forests, LambdaMART and gradient boosted regression trees) have come to dominate learning to rank systems in practice, as they provide the ability to learn from large scale data while generalizing well to additiona...More



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