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Proposal for the 1~(st) Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR)

机译:1〜(ST)跨学科研讨会关于算法选择和荟萃学习的跨学科研讨会(AMIR)

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The algorithm selection problem describes the challenge of identifying the best algorithm for a given problem space. In many domains, particularly artificial intelligence, the algorithm selection problem is well stadied, and various approaches and tools exist to tackle it in practice. Especially through meta-learning impressive performance improvements have been achieved. The information retrieval (IR) community, however, has paid little attention to the algorithm selection problem, although the problem is highly relevant in information retrieval. This workshop will bring together researchers from the fields of algorithm selection and meta-learning as well as information retrieval. We aim to raise the awareness in the IR community of the algorithm selection problem; identify the potential for automatic algorithm selection in information retrieval; and explore possible solutions for this context. In particular, we will explore to what extent existing solutions to the algorithm selection problem from other domains can be applied in information retrieval, and also how techniques from IR can be used for automated algorithm selection and meta-learning.
机译:算法选择问题描述了识别给定问题空间的最佳算法的挑战。在许多域中,特别是人工智能,算法选择问题很好地,存在各种方法和工具在实践中解决它。特别是通过元学习令人印象深刻的性能改进。然而,信息检索(IR)社区对算法选择问题几乎没有注意,尽管问题在信息检索中具有高度相关性。该研讨会将从算法选择和元学习领域带来研究人员以及信息检索。我们的目标是提高算法选择问题的IR社区的意识;确定信息检索中自动算法选择的潜力;并探索此背景的可能解决方案。特别是,我们将探索从其他域的算法选择问题的现有解决方案的程度,可以应用于信息检索,以及来自IR的技术如何用于自动算法选择和元学习。

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