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Filtering by: Creator Zurek, Wojciech H. Remove constraint Creator: Zurek, Wojciech H. Advisor Huang, Liang Remove constraint Advisor: Huang, Liang

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  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation

  • Structured Neural Models for Natural Language Processing

    Creator:
    Ma, Mingbo
    Abstract:
    Most tasks in natural language processing (NLP) involves structured information from both input (e.g., a sentence or a paragraph) and output (e.g., a tag sequence, a parse tree or a translated sentence). While neural models achieve great successes in other domains such as computer vision, applying those frameworks to NLP...
    Resource Type:
    Dissertation
    Full Text:
    patterns on trees. Word concatenation always starts with m, while h, g, and g2 denote parent, grand parent

  • Advances in Simultaneous Translation

    Creator:
    Zheng, Renjie
    Abstract:
    Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
    Resource Type:
    Dissertation
    Full Text:
    word embedding of dx dimensions, and produces a new sequence of hidden states h = f(x) = (h1, ..., hn