文章基本信息

标题：Learning Better Data Representation Using Inference-Driven Metric Learning
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作者：Paramveer S. Dhillon ; Partha Pratim Talukdar ; Koby Crammer 等
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2010
卷号：2010
出版社：ACL Anthology
摘要：We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by previously proposed unsupervised dimensionality reduction methods (e.g., PCA). Through a variety of experiments on different realworld datasets, we find IDML-IT, a semisupervised metric learning algorithm to be the most effective.