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半直推式排序

Half transductive ranking
课程网址: http://videolectures.net/aistats2010_weston_htr/  
主讲教师: Jason Weston
开课单位: 脸书公司
开课时间: 2010-06-03
课程语种: 英语
中文简介:
摘要研究了给定一个以前没有见过的查询,对一组固定条目进行排序的标准检索任务,并将其作为半转换排序问题。任务是可转换的,因为项目集是固定的。转换表示(学习每个示例的向量表示)允许生成高度非线性的嵌入,这些嵌入捕获对象关系而不依赖于特定的特性选择,并且只需要相对简单的优化。不幸的是,它们没有直接的样本外扩展。另一方面,归纳方法允许表示未知查询。我们描述了这种设置的算法,这些算法具有转换和归纳方法的优点,并且可以应用于非监督(基于重构或基于图形)和监督排序设置。我们的实证研究表明,我们的方法在这三个任务上都有很强的表现。
课程简介: We study the standard retrieval task of ranking a fixed set of items given a previously unseen query and pose it as the half transductive ranking problem. The task is transductive as the set of items is fixed. Transductive representations (where the vector representation of each example is learned) allow the generation of highly nonlinear embeddings that capture object relationships without relying on a specific choice of features, and require only relatively simple optimization. Unfortunately, they have no direct out-of-sample extension. Inductive approaches on the other hand allow for the representation of unknown queries. We describe algorithms for this setting which have the advantages of both transductive and inductive approaches, and can be applied in unsupervised (either reconstruction-based or graph-based) and supervised ranking setups. We show empirically that our methods give strong performance on all three tasks.
关 键 词: [半直推式; 排序
课程来源: 视频讲座网
最后编审: 2020-01-13:chenxin
阅读次数: 30