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Filtering by: Creator Williford, Russell S. Remove constraint Creator: Williford, Russell S. Subject Machine learning Remove constraint Subject: Machine learning

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  • Toward harnessing user feedback for machine learning

    Creator:
    Stumpf, Simone, Rajaram, Vidya, Li, Lida, Burnett, Margaret, 1949-, Dietterich, Thomas Glen, Sullivan, Erin, Drummond, Russell, and Herlocker, Jonathan Lee
    Abstract:
    There has been little research into how end users might be able to communicate advice to machine learning systems. If this resource--the users themselves--could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users' understanding and trust of the system could improve...
    Resource Type:
    Technical Report
    Full Text:
    Simone Stumpf, Vidya Rajaram, Lida Li, Margaret Burnett, Thomas Dietterich, Erin Sullivan, Russell

  • Special Nuclear Material Analysis Using Temporal Gamma-Ray Spectroscopy and Machine Learning Methods

    Creator:
    Curtis, Jessica R.
    Abstract:
    Following thermal neutron induced fission, supervised machine learning and temporal gamma-ray spectroscopy methods were used to identify differences in the delayed gamma-ray spectra of Pu-239 and U-235. The temporal gamma-ray spectroscopy method takes advantage of the time-dependent decay of fission products. Employing Spearman's rank-order correlation coefficient and without prior knowledge...
    Resource Type:
    Masters Thesis
    Full Text:
    MeV of Pu-239 and U-235. Individual rho (ρs) values and their respective differences (∆ρs) were used

  • Constraining Bayesian network learning with qualitative models

    Creator:
    Altendorf, Eric E.
    Abstract:
    Machine learning encompasses probabilistic and statistical techniques that can build models from large quantities of extensional information (examples) with minimal dependence on intensional information (domain knowledge). This focus of machine learning is reflected in the never-ending quest for "off-the-shelf" classifiers. To generalize to unseen data, however, we must make use...
    Resource Type:
    Masters Thesis
    Full Text:
    Distribution (Alam and Wallenius) 76 8.4 Relationships and Discussion .................... 76 8.4.1 m* and s

  • Representations and algorithms for efficient inference in Bayesian networks

    Creator:
    Takikawa, Masami
    Abstract:
    Bayesian networks are used for building intelligent agents that act under uncertainty. They are a compact representation of agents' probabilistic knowledge. A Bayesian network can be viewed as representing a factorization of a full joint probability distribution into the multiplication of a set of conditional probability distributions. Independence of causal...
    Resource Type:
    Dissertation
    Full Text:
    NP-hard [Russell and Norvig, 1995]. For example, none of the existing exact inference systems are

  • Emerging Technologies in Fisheries Science: A Transdisciplinary Report

    Creator:
    Firl, Alrik, Haven, Katlyn, and Newton, Samm
    Abstract:
    The Pacific Coast Groundfish Fishery harvests a diverse and large grouping of fishes, but it did not become heavily fished until around WWII. This makes the groundfish fishery a comparatively young fishery. Despite its youth, it is one of the largest and most lucrative fisheries in Oregon—with a current harvest...
    Resource Type:
    Research Paper
    Full Text:
    -independent surveys did not begin until the late 70’s and were geared towards more efficient harvest, as the

  • 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:
    , r t i) } , t = 1 . . . Li and s t i, a t i, and rti are the state, action and reward at time t

  • Combining coordination mechanisms to improve performance in multi-robot teams

    Creator:
    Nasroullahi, Ehsan
    Abstract:
    Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
    Resource Type:
    Masters Thesis
    Full Text:
    agents are required to observe each POI. Agents using D � S � IDEAS outperform all other methods once the

  • 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

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    material are those of the author(s) and do not necessarily reflect the views of the National Science

  • Monte-Carlo planning for probabilistic domains

    Creator:
    Bjarnason, Ronald V.
    Abstract:
    This thesis presents a progression of novel planning algorithms that culminates in a new family of diverse Monte-Carlo methods for probabilistic planning domains. We provide a proof for performance guarantees and analyze how these algorithms can resolve some of the shortcomings of traditional probabilistic planning methods. The direct policy search...
    Resource Type:
    Dissertation
    Full Text:
    of (a) standard rollouts and (b) nested rollouts and (c). A heuristic, h, evaluates a state, s, with