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Filtering by: Creator Swanson, Thomas B. Remove constraint Creator: Swanson, Thomas B. Contributor advisor sim Dietterich, Thomas G. Remove constraint Contributor advisor sim: Dietterich, Thomas G.

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  • 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:
    : -'<"-----~~-_.,,__, ____,,._...,...---:::....::....-~-vo""'1,...L...L."":>.....>,E¥"W":~""".,,.=----------- Thomas G

  • 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:
    Fine-grained Object Classification of Arthropod Specimens Abstract approved: Thomas G. Dietterich

  • 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:
    : Simulator-Defined MDP Planning with Applications in Natural Resource Management Abstract approved: Thomas

  • Learning functional descriptions from examples

    Creator:
    Flann, Nicholas S.
    Abstract:
    The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility is severe when learning functional concepts and explains why previous researchers have...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approve Thomas G. Dietterich. The task of inductive learning from examples places constraints on

  • An empirical study into learning through experimentation

    Creator:
    Ruff, Ritchey Alvin
    Abstract:
    A key aspect of how we understand the world revolves around an ability to manipulate our surroundings to experiment. From the scientific method through theories of child development, the ability to experiment is deemed critical; however, few studies have been performed to understand the strengths and weaknesses of different experimental...
    Resource Type:
    Dissertation
    Full Text:
    Redacted for privacy Abstract approved. Thomas G. Dietterich A key aspect of how we understand the world

  • Learning cost-sensitive diagnostic policies from data

    Creator:
    Zubek, Valentina Bayer
    Abstract:
    In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...
    Resource Type:
    Dissertation
    Full Text:
    . Title: Learning Cost-Sensitive Diagnostic Policies from Data. Abstract approved: Thomas G. Dietterich

  • A study of distance-based machine learning algorithms

    Creator:
    Wettschereck, Dietrich
    Abstract:
    Distance-based algorithms are machine learning algorithms that classify queries by computing distances between these queries and a number of internally stored exemplars. Exemplars that are closest to the query have the largest in uence on the classi cation assigned to the query. Two speci c distance-based algorithms, the nearest neighbor...
    Resource Type:
    Dissertation
    Full Text:
    Distance-Based Machine Learning Algorithms Abstract approved: Thomas G. Dietterich Distance-based

  • Column Time Warping with Neighborhood Distortion Cost

    Creator:
    Kucey, Brennan Mark
    Abstract:
    Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
    Resource Type:
    Honors College Thesis
    Full Text:
    : ______________________________________________________ Thomas Dietterich The Cornell Laboratory of Ornithology coordinates the eBird

  • A specialized ATMS for equivalence relations

    Creator:
    Koff, Caroline Nan
    Abstract:
    A specialized ATMS for efficiently computing equivalence relations in multiple contexts is introduced. This specialized ATMS overcomes the problems with existing solutions to reasoning with equivalence relations. The most direct implementation of an equivalence relation in the ATMS-encoding the reflexive, transitive, and symmetric rules in the consumer architecture-produces redundant equality...
    Resource Type:
    Masters Thesis
    Full Text:
    for privacy Thomas G. Dietterich. A specialized ATMS for efficiently computing equivalence relations

  • Three methods for estimating subpixel cover fractions in coarse resolution imagery

    Creator:
    Damon, Diane L.
    Abstract:
    Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
    Resource Type:
    Masters Thesis
    Full Text:
    Estimating Subpixel Cover Fractions in Coarse Resolution Imagery. Abstract approved: Thomas G. Dietterich