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Bi-granularity Adversarial Training for Non-factoid Answer Retrieval

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  1. Chapter and Conference Paper

    Uncovering Locally Discriminative Structure for Feature Analysis

    Manifold structure learning is often used to exploit geometric information among data in semi-supervised feature learning algorithms. In this paper, we find that local discriminative information is also of imp...

    Sen Wang, Fei** Nie, **aojun Chang, Xue Li in Machine Learning and Knowledge Discovery i… (2016)

  2. Chapter and Conference Paper

    Unsupervised Feature Analysis with Class Margin Optimization

    Unsupervised feature selection has been attracting research attention in the communities of machine learning and data mining for decades. In this paper, we propose an unsupervised feature selection method seek...

    Sen Wang, Fei** Nie, **aojun Chang in Machine Learning and Knowledge Discovery i… (2015)

  3. Chapter and Conference Paper

    Modeling Relations and Their Mentions without Labeled Text

    Several recent works on relation extraction have been applying the distant supervision paradigm: instead of relying on annotated text to learn how to predict relations, they employ existing knowledge bases (KB...

    Sebastian Riedel, Limin Yao, Andrew McCallum in Machine Learning and Knowledge Discovery i… (2010)