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Filtering by: Creator Chuang, Ching-Ta Remove constraint Creator: Chuang, Ching-Ta Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Optimal load and resource balance in internet distributed systems

    Creator:
    Nishida, Hiroshi
    Abstract:
    A distributed system is a network of multiple autonomous computational nodes designed primarily for performance scalability and robustness. The performance of a distributed system depends critically on how tasks and resources are distributed among the nodes. Thus, a main thrust in distributed system research is to design schemes for distributing...
    Resource Type:
    Dissertation

  • A linear equation model for a family of interconnection networks

    Creator:
    Larson, Shawn M.
    Abstract:
    The most important part of parallel computation is communication. Except in the most embarassingly parallel examples, processors cannot work cooperatively to solve a problem unless they can communicate. One way to solve the problem of communication is to use an interconnection network. Processors are located at nodes of the network,...
    Resource Type:
    Dissertation
    Full Text:
    complete binary tree of 2n 1 nodes. (The proof is incorrect.) Cheng and Chuang [13] have designed

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    . In 8 0 20 40 60 80 100 Sentence BLEU 0.0% 1.0% 2.0% 3.0% Pe rc en ta ge k=1 k=3 k=5 k=7 k

  • Embeddings in parallel systems

    Creator:
    Kwon, Younggeun
    Resource Type:
    Dissertation

  • 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

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation

  • Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

    Creator:
    Vu, Trung
    Abstract:
    Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
    Resource Type:
    Dissertation