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Filtering by: Creator Katz, Richard W. Remove constraint Creator: Katz, Richard W. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Topics in toroidal interconnection networks

    Creator:
    Broeg, Robert Richard
    Resource Type:
    Dissertation
    Full Text:
    THE THESIS OF Robert Richard Broeg, SDS for the degree of Doctor of Philosophy in Computer

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Robin W. Hess for the

  • Designing and understanding information retrieval systems using collaborative filtering in an academic library environment

    Creator:
    Jung, Seikyung
    Abstract:
    Accessing information on the Web has become ingrained into our daily lives, and we seek information from many different sources, including conference and journal publications, personal web pages, and others. Increasingly, web-based information retrieval systems such as web-based search engines, library on-line catalog systems, and subscription-based federated search systems are...
    Resource Type:
    Dissertation

  • Variational Typing and Its Applications

    Creator:
    Chen, Sheng
    Abstract:
    The study of variational typing originated from the problem of type inference for variational programs, which encode numerous different but related plain programs. In this dissertation, I present a sound and complete type inference algorithm for inferring types of all plain programs encoded in variational programs. The proposed algorithm runs...
    Resource Type:
    Dissertation
    Full Text:
    type inference algorithm W . . . . . . . . . . . . . . . . . . . . . . 24 2.4 VLC syntax

  • 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
    Full Text:
    modeled by some statistical model with parameters w. So F can also be written as Fw. This problem is

  • Nonuniform Sampling Of Band-limited Functions

    Creator:
    Al-Hammali, Hussain Y.
    Abstract:
    In this thesis, we will study certain generalizations of the classical Shannon Sampling Theorem, which allows for the reconstruction of a pi-band-limited, square-integrable function from its samples on the integers. J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which includes nonuniform and...
    Resource Type:
    Dissertation
    Full Text:
    . A function f is in the Paley-Wiener space PWp ⇡ , 1  p  1 if f(z) = R ⇡ �⇡ g(w)e izwdw, z 2 C

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 A recursive neural network for a small binary tree. The same weights W are used at each

  • Event detection with forward-backward recurrent neural networks

    Creator:
    Ghaeini, Mohammad Reza
    Abstract:
    Automatic event extraction from natural text is an important and challenging task for natural language understanding. Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But such efforts, like tradition methods, have so far only focused on...
    Resource Type:
    Masters Thesis
    Full Text:
    the goal is to learn a set of wight matrices W s and bias terms bs. The output of a simple layer in a

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    ) = w · φ(a), where w is the weight vector and φ(·) is a predefined feature function. Note that the

  • Learning ranking functions for efficient search

    Creator:
    Xu, Yuehua
    Abstract:
    This dissertation explores algorithms for learning ranking functions to efficiently solve search problems, with application to automated planning. Specifically, we consider the frameworks of beam search, greedy search, and randomized search, which all aim to maintain tractability at the cost of not guaranteeing completeness nor optimality. Our learning objective for...
    Resource Type:
    Dissertation
    Full Text:
    with a feature vector f(v) and nodes are ranked according to w · f(v) where w is a weight vector. Each