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  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    Azimi for the degree of Doctor of Philosophy in Computer Science presented on September 5, 2012. Title

  • Active learning of constraints for semi-supervised clustering

    Creator:
    Xiong, Sicheng
    Abstract:
    Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
    Resource Type:
    Masters Thesis
    Full Text:
    Master of Science in Computer Science presented on April 25, 2013. Title: Active Learning of

  • On the limits of mutation analysis

    Creator:
    Gopinath, Rahul
    Abstract:
    Mutation analysis is the gold standard for evaluating test-suite adequacy. It involves exhaustive seeding of all small faults in a program and evaluating the effectiveness of test suites in detecting these faults. Mutation analysis subsumes numerous structural coverage criteria, approximates fault detection capability of test suites, and the faults produced...
    Resource Type:
    Dissertation
    Full Text:
    On the Limits of Mutation Analysis AN ABSTRACT OF

  • Reinforcement learning-based off-equilibrium incentives to approximate the VCG mechanism

    Creator:
    Moissinac, Béatrice
    Abstract:
    Auctions are used to solve resource allocation problem between many agents and many items in real-world settings. Unfortunately, in most cases, it is possible for selfish agents to manipulate the system for their own interest at the expense of the social welfare. Such manipulation can be prevented using the Vickrey-Clarke-Groves...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Computer Science presented on November 22, 2013. Title: Reinforcement

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    problems. Finally, we present our analysis and discussion on the results we got. • We conclude the thesis

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    of Philosophy in Computer Science presented on May 08, 2006. Title: Model Based Approximation

  • Topological analysis, visualization, and design of vector fields on surfaces

    Creator:
    Chen, Guoning
    Abstract:
    Analysis, visualization, and design of vector fields on surfaces have a wide variety of major applications in both scientific visualization and computer graphics. On the one hand, analysis and visualization of vector fields provide critical insights to the flow data produced from simulation or experiments of various engineering processes. On...
    Resource Type:
    Dissertation
    Full Text:
    follows. Vector Field Analysis (ECG): The mathematical foundations of time-independent vector fields on

  • A linear equation model for a family of interconnection networks

    Creator:
    Larson, Shawn M.
    Abstract:
    The most important part of parallel computation is communication. Except in the most embarassingly parallel examples, processors cannot work cooperatively to solve a problem unless they can communicate. One way to solve the problem of communication is to use an interconnection network. Processors are located at nodes of the network,...
    Resource Type:
    Dissertation
    Full Text:
    Computer Science pre­ sented on May 4, 1995. Title: A Linear Equation Model for a Family of

  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    degree of Doctor of Philosophy in Computer Science presented on January 27, 2017. Title: Domain

  • Analytical and visual tools for robot kinematics

    Creator:
    Harris-Coppola, Marcia M.
    Abstract:
    Computer control of a robot arm's motion requires kinematic algorithms for relating the state of a particular arm's joints to the position and orientation of its tool in three-dimensional space. To design such algorithms requires mathematical formulation of the kinematics of the arm. The resulting long, tedious algebraic manipulations suggest...
    Resource Type:
    Masters Thesis
    Full Text:
    need for graphic as well as mathematical tools. Here we focus on kinematics. All three of these areas