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Filtering by: Creator Kent, Adam J. R. Remove constraint Creator: Kent, Adam J. R. Subject Machine learning Remove constraint Subject: Machine learning

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  • Towards a national map of soil liquefaction susceptibility : modeling with heuristic and geotechnical methods

    Creator:
    Lindsley, Adam E.
    Abstract:
    This study investigates the use of predictive mapping techniques as well as geotechnical criteria in developing a multiregional soil liquefaction model and subsequent maps. The maps were produced using National Cooperative Soil Survey data, in the gSSURGO format, combined with soil liquefaction data gathered from studies, articles, and traditional seismic...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Adam E. Lindsley

  • The Pursuit of Hoppiness : Propelling Hop into the Genomic Era

    Creator:
    Hill, Steven T.
    Abstract:
    Hop (Humulus lupulus L. var lupulus) is a plant of great cultural significance, used as a medicinal herb for thousands of years, and for flavor and as a preservative in brewing beer. Studies of the medicinal effects of the unique compounds produced by hop have led to interest from the...
    Resource Type:
    Masters Thesis
    Full Text:
    Chapter 3: Genomics of the Hop Pseudo-Autosomal Regions S. T. Hill, J. Coggins, A. Liston

  • Structured gradient boosting

    Creator:
    Parker, Charles (Charles Lincoln)
    Abstract:
    The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
    Resource Type:
    Dissertation
    Full Text:
    generally, a vector 8 of real numbers1 of some fixed size d so that X = ℜd. If Y = ℜ, then this is a

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation
    Full Text:
    Qualcomm Corp R&D. I am also grateful to my good friends and colleagues, in university and my internships

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    1 µpl′ ·xp) , ν (0) j = σ( ∑ l ∑ i ∑ p∈i 1 |i|µ (0) pl Wijl + bj + ∑ j′W ′ jj′r t−1 j

  • New learning modes for sequential decision making

    Creator:
    Judah, Kshitij
    Abstract:
    This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
    Resource Type:
    Dissertation
    Full Text:
    := T ∪ GetPracticeTrajectories(θ) 6: for i = 1:n do 7: λ = λi //choose a value of λ 8: θi = argmaxθ Jλ

  • Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

    Creator:
    Briggs, Forrest
    Abstract:
    We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
    Resource Type:
    Dissertation
    Full Text:
    University. We would also like to thank Matthew Betts, Sarah Frey, Adam Hadley, and Jay Sexsmith for their

  • Methods for cost-sensitive learning

    Creator:
    Margineantu, Dragos D.
    Abstract:
    Many approaches for achieving intelligent behavior of automated (computer) systems involve components that learn from past experience. This dissertation studies computational methods for learning from examples, for classification and for decision making, when the decisions have different non-zero costs associated with them. Many practical applications of learning algorithms, including transaction...
    Resource Type:
    Dissertation
    Full Text:
    [63]: 11 K Yopt = argmin R(yJx) = argmin L P(yjJx)C(y, yj)- yEY yEY j=l (2.3) Leth be a

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    recordings of birdsong are collected by unattended microphones in the H. J. Andrews Experimental Forest. The

  • Machine learning for computer architecture design and optimization

    Creator:
    Penney, Drew
    Abstract:
    Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
    Resource Type:
    Dissertation
    Full Text:
    comparison (after P&R). . . . . . . . . . . . . . . . . . . . . . . . . 90 4.15 Synthetic Scaling for NoC