Xiaojin Zhu [5]Xiaojing Zhu [1]
  1.  63
    Can semi-supervised learning explain incorrect beliefs about categories?Charles W. Kalish, Timothy T. Rogers, Jonathan Lang & Xiaojin Zhu - 2011 - Cognition 120 (1):106-118.
    Three experiments with 88 college-aged participants explored how unlabeled experiences—learning episodes in which people encounter objects without information about their category membership—influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then made a large number of unsupervised categorization decisions about new items. In all three experiments, the unsupervised experience altered participants’ implicit and explicit mental category boundaries, their explicit beliefs about the most representative members of each category, and even their memory (...)
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  2.  81
    Human Semi-Supervised Learning.Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu - 2013 - Topics in Cognitive Science 5 (1):132-172.
    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and (...)
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  3. Semi-supervised learning is observed in a speeded but not an unspeeded 2D categorization task.Timothy T. Rogers, Charles Kalish, Bryan R. Gibson, Joseph Harrison & Xiaojin Zhu - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society.
  4.  6
    The Role of Perceptual Interference, Semantic Interference, and Relational Integration in the Development of Analogical Reasoning.Xiao Yu, Liuna Geng, Yinghe Chen, Congcong Han & Xiaojing Zhu - 2020 - Frontiers in Psychology 11.
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  5. Neural Optimization and Dynamic Programming-Algorithm Analysis and Application Based on Chaotic Neural Network for Cellular Channel Assignment.Xiaojin Zhu, Yanchun Chen, Hesheng Zhang & Jialin Cao - 2006 - In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer Verlag. pp. 991-996.