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Filtering by: Creator Palo, D. Remove constraint Creator: Palo, D. Advisor Dietterich, Thomas G. Remove constraint Advisor: 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:
    be rigorous. He has been very influential in my thinking. I owe special debts to Bruce D' Ambrosio

  • An investigation of the search space of Lenat's AM program

    Creator:
    Mishra, Prafulla K.
    Abstract:
    AM is a computer program written by Doug Lenat that discovers elementary mathematics starting from some initial knowledge of set theory. The success of this program is not clearly understood. This work is an attempt to explore the search space of AM in order to understand the success and eventual...
    Resource Type:
    Masters Thesis
    Full Text:
    b) restrict range and name domain. 3.1.1 Restrict Domain and Name Range Given a function f : D ÷ R

  • 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:
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  • Just enough die-level functional test : optimizing IC test via machine learning and decision theory

    Creator:
    Fountain, Tony R.
    Abstract:
    This research explores the hypothesis that methods from decision theory and machine learning can be combined to provide practical solutions to current manufacturing control problems. This hypothesis is explored by developing an integrated approach to solving one manufacturing problem - the optimization of die-level functional test. An integrated circuit (IC)...
    Resource Type:
    Dissertation

  • Image features and learning algorithms for biological, generic and social object recognition

    Creator:
    Zhang, Wei
    Abstract:
    Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
    Resource Type:
    Dissertation
    Full Text:
    . James Begole, Dr. Juan Liu and Dr. Maurice Chu in the Palo Alto Research Center. It was such a

  • Understanding and improving error-correcting output coding

    Creator:
    Kong, Eun Bae
    Abstract:
    Error-correcting output coding (ECOC) is a method for converting a k-classsupervised learning problem into a large number L of two-class supervised learningproblems and then combining the results of these L evaluations. Previous researchhas shown that ECOC can dramatically improve the classi cation accuracy of supervisedlearning algorithms that learn to classify...
    Resource Type:
    Dissertation
    Full Text:
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  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation

  • Probabilistic models for quality control in environmental sensor networks

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
    Resource Type:
    Dissertation
    Full Text:
    environmental sensor. The baseline function b(qh, d) analyzed a historical record of observations from the

  • 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:
    supervised learning. Formally, given a sample of labeled examples (x; y) drawn from a distribution D(x; y

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    the CNN Agent from Chapters 6 and 7 . . . . . . . . . . . . . 153 D What domain to study? StarCraft