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Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist… Expand A new recurrent neural network based language model (RNN LM) with applications to speech recognition is presented. Results… Expand schema. For a general summary, there are normative descriptions of stages of L2 proficiency that were drawn up in as atheoretical… Expand This article presents a general class of associative reinforcement learning algorithms for connectionist networks containing… Expand This review summarizes a range of theoretical approaches to language acquisition. It argues that language representations emerge… Expand Contents: Preface. J.R. Anderson, C. Lebiere, Introduction. J.R. Anderson, C. Lebiere, Knowledge Representation. J.R. Anderson, C… Expand Part 1 Introduction: matter and method space and semantic potential negative evidence and language learning the modelling… Expand Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very… Expand Author(s): Freeman, Walter J, III | Abstract: Paul Smolensky's marvelous neologisitc epithet "neuromacho" should not be allowed… Expand