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Filtering by: Creator Hilliard, Richard F. Remove constraint Creator: Hilliard, Richard F. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Degree Name Doctor of Philosophy (Ph.D.) Remove constraint Degree Name: Doctor of Philosophy (Ph.D.)

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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

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    (BO) methods are often used to optimize an unknown function f(·) that is costly to evaluate. They

  • 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:
    generalization allows for functions f that, while still band-limited, need not be square-integrable but may have

  • Reinforcement learning for job-shop scheduling

    Creator:
    Zhang, Wei, 1960-
    Resource Type:
    Dissertation
    Full Text:
    to learn scheduling knowledge. [Hilliard et al., 1988] showed experimentally that optimal rules for

  • Optimization of seasonal irrigation scheduling by genetic algorithms

    Creator:
    Canpolat, Necati
    Abstract:
    In this work, we first introduce a novel approach to the long term irrigation scheduling using Genetic Algorithms (GAs). We explore the effectiveness of GAs in the context of optimizing nonlinear crop models and describe application requirements and implementation of the technique. GAs were found to converge quickly to near-optimal...
    Resource Type:
    Dissertation
    Full Text:
    Constant penalty function with c=30. F(x) is the fitness value after penalty, and f(x) is the fitness

  • 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:
    (trained and tested with gold POS tags). . . . . . . . . . . . . . . . . . 47 3.5 Test F-scores for

  • 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

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation

  • Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

    Creator:
    Marcon dos Santos, Gilberto
    Abstract:
    This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
    Resource Type:
    Dissertation

  • Variational Satisfiability Solving

    Creator:
    Young, Jeffrey M.
    Abstract:
    Over the last two decades, satisfiability and satisfiability-modulo theory (SAT/SMT) solvers have grown powerful enough to be general purpose reasoning engines throughout software engineering and computer science. However, most practical use cases of SAT/SMT solvers require not just solving a single SAT/SMT problem, but solving sets of related SAT/SMT problems....
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . 31 4.3 Possible plain models for variants of f . . . . . . . . . . . . . . . . . . . 36 4.4