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Filtering by: Creator Tsui, Daniel C. N. Remove constraint Creator: Tsui, Daniel C. N. Advisor Dietterich, Thomas G. Remove constraint Advisor: Dietterich, Thomas G.

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  • Disjunctions in forward chaining logic programming

    Creator:
    Corpron, Daniel R.
    Abstract:
    A forward-chaining logic programming system (FORLOG) has been developed at Oregon State University. This system coupled with an assumption-based truth maintenance system (ATMS), provides an alternative to the logic programming paradigm of backward-chaining with Horn clauses. To compare FORLOG to this paradigm, we define a subset of FORLOG, called mini-FORLOG,...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract of the Thesis of Daniel R. Corpron for the degree of Master of Science in Computer Science

  • 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:
    AN ABSTRACT OF THE THESIS OF Daniel L. K. Forrest for the

  • 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:
    drawn to shrink the confidence interval as quickly as possible? (c) how can we find the optimal policy

  • 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:
    and can also be applied to many other machine learning problems. c©Copyright by Liping Liu June 10

  • 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:
    xy xy s xy n xy ij N N M L c c c c

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    i s i n g s t u d e n t s h e n p r o j e c t T a s k T r a c e r c o m m e n t s o n t h e s i

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    isolate N data points. Let c(N) = 2H(N − 1)− 2(N − 1)/N , where H(N) is the N th harmonic number ≈ ln(N

  • 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:
    diagnostic policies that seek to minimize the expected total cost of diagnosis. c Copyright by Valentina

  • Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

    Creator:
    Liu, Si
    Abstract:
    Anomaly detection aims at detecting the points that appear different than the majority of the data, such that they are suspected to be generated from a different distribution. Anomaly detectors have been applied in many different fields, such as detecting fraudulent behaviors in bank transaction, finding broken sensors in a...
    Resource Type:
    Dissertation
    Full Text:
    iForest and s(d(xi)) is the anomaly score calculated based on d(xi) given by s(d(xi)) = 2 � d(xi)c(n) and

  • Efficient training and feature induction in sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
    Resource Type:
    Dissertation
    Full Text:
    range dependencies in sequences. c©Copyright by Guohua Hao July 21, 2009 All Rights Reserved