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Filtering by: Creator Kaufmann, Philip R. Remove constraint Creator: Kaufmann, Philip R. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Automated decomposition of complex parts for manufacturing with advanced joining processes

    Creator:
    Massoni, Brandon R.
    Abstract:
    Recent advancements in joining operations and additive manufacturing now allow complex metal parts to be built up from raw materials, as opposed to being machined down from solid blocks. This not only opens up the design space, but also allows for much more efficient manufacturing. By decomposing a complex part...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Brandon R

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    learn- ing algorithm. In our approach, we learn the models P (s′|s, a) and R(s′|s, a), and then use

  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation
    Full Text:
    almost as good as mask R-CNN without depending on a two-stage framework. Note that the training of the

  • 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:
    percentage r=0.20. 90 4-7 Relative fitness penalty scaled by fitness, f(x) 91 4-8 Relative distance based

  • Analytical Methods for Improving Causal Inference

    Creator:
    Sinha, Meghamala
    Abstract:
    Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
    Resource Type:
    Dissertation

  • Shrunken learning rates do not improve AdaBoost on benchmark datasets

    Creator:
    Forrest, Daniel L. K.
    Abstract:
    Recent work has shown that AdaBoost can be viewed as an algorithm that maximizes the margin on the training data via functional gradient descent. Under this interpretation, the weight computed by AdaBoost, for each hypothesis generated, can be viewed as a step size parameter in a gradient descent search. Friedman...
    Resource Type:
    Masters Thesis
    Full Text:
    International Conference on Machine Learn- ing, pages 148-146. Morgan Kaufmann. [7] Freund, Y. and Schapire, R

  • Reinforcement learning for job-shop scheduling

    Creator:
    Zhang, Wei, 1960-
    Resource Type:
    Dissertation

  • Topics in toroidal interconnection networks

    Creator:
    Broeg, Robert Richard
    Resource Type:
    Dissertation
    Full Text:
    = r- c-01 k,. T is a graph with N nodes, numbered 0 N 1. Each node of T is labeled with a mixed

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 4.6 Plots of V UCB(λ ν lower) R , VR − V UCB(λνlower) R , and V UCB(λνlower) C on the vertical

  • Resource placement, data rearrangement, and Hamiltonian cycles in torus networks

    Creator:
    Bae, Myung Mun
    Abstract:
    Many parallel machines, both commercial and experimental, have been/are being designed with toroidal interconnection networks. For a given number of nodes, the torus has a relatively larger diameter, but better cost/performance tradeoffs, such as higher channel bandwidth, and lower node degree, when compared to the hypercube. Thus, the torus is...
    Resource Type:
    Dissertation
    Full Text:
    Approved by Committee: Major Professor (Bella Bose) Committee Member (Curtis R. Cook) Committee