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      Advances in Information Retrieval 

      Curriculum Learning Strategies for IR

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      Springer International Publishing

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          Curriculum learning

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            Learning and development in neural networks: the importance of starting small.

             Jeffrey Elman (1993)
            It is a striking fact that in humans the greatest learning occurs precisely at that point in time--childhood--when the most dramatic maturational changes also occur. This report describes possible synergistic interactions between maturational change and the ability to learn a complex domain (language), as investigated in connectionist networks. The networks are trained to process complex sentences involving relative clauses, number agreement, and several types of verb argument structure. Training fails in the case of networks which are fully formed and 'adultlike' in their capacity. Training succeeds only when networks begin with limited working memory and gradually 'mature' to the adult state. This result suggests that rather than being a limitation, developmental restrictions on resources may constitute a necessary prerequisite for mastering certain complex domains. Specifically, successful learning may depend on starting small.
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              Learning to Rank for Information Retrieval

               Tie-Yan Liu (2009)
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                Author and book information

                Book
                978-3-030-45438-8
                978-3-030-45439-5
                2020
                10.1007/978-3-030-45439-5

                http://www.springer.com/tdm

                Book Chapter
                2020
                April 08 2020
                : 699-713
                10.1007/978-3-030-45439-5_46

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