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Filtering by: Creator Ortíz-Lozano, Leonardo D. Remove constraint Creator: Ortíz-Lozano, Leonardo D. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Weakly Supervised Learning for Activity Recognition from Time Series Data

    Creator:
    Guan, Xinze
    Abstract:
    The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...
    Resource Type:
    Dissertation
    Full Text:
    Step Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 D Maximization Step Details

  • A SAT-based planning framework for optimizing resource production

    Creator:
    Ventura, Christopher
    Abstract:
    Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . 67 D Compact Resource Production Problem . . . . . . . . . . . . . . . . . 76 LIST OF FIGURES

  • Synthetic instrument generation : generating novel instrument timbres with a genetic algorithm

    Creator:
    Knowlton, John
    Abstract:
    The use of genetic algorithms to compose music and generate sounds is an area of interest in the artificial intelligence field. Music and instrument sounds have known rules and structures that can be followed which make them well-suited for genetic algorithms. However, genetic algorithms still struggle to generate sounds comparable...
    Resource Type:
    Honors College Thesis

  • Semantic embodied navigation : developing agents that navigate from language and vision

    Creator:
    Krantz, Jacob
    Abstract:
    Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
    Resource Type:
    Dissertation
    Full Text:
    Language Navigators From Discrete to Continuous Simulation 137 TABLE OF CONTENTS (Continued) Page D

  • Variational Satisfiability Solving

    Creator:
    Young, Jeffrey M.
    Abstract:
    Over the last two decades, satisfiability and satisfiability-modulo theory (SAT/SMT) solvers have grown powerful enough to be general purpose reasoning engines throughout software engineering and computer science. However, most practical use cases of SAT/SMT solvers require not just solving a single SAT/SMT problem, but solving sets of related SAT/SMT problems....
    Resource Type:
    Dissertation
    Full Text:
    . Variational cores are key to our approach, and enable the preservation of shared terms between variants. (d

  • 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:
    on (a) Cart- pole (b) Bicycle balancing (c) Wargus (d) Driving Domain. . . . . . . . . 80 4.4

  • Assisting Sustainability Analysis of Forest Bioenergy Supply Chains using Mathematical Optimization

    Creator:
    Sadeghi, Javad
    Abstract:
    Changes in the global climate and forest management practices have given rise to increasing numbers and severity of wildfires. More than five million acres burned in the United States in 2017, while in Canada 7.4 million acres burned. In particular, an increasing amount of dead woody biomass is a key...
    Resource Type:
    Masters Thesis
    Full Text:
    sustainable performance of a product (Giddings, Hopwood, & O’Brien, 2002; Lozano, 2008). 1.2 Background

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    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:
    industrial R&D, documentation and the patent application process, which are valuable for my future career

  • Stake-Free Evaluations of Black-Box Optimization and Spatio-Temporal Graph Network Algorithms

    Creator:
    Merrill, Erich, III
    Abstract:
    Papers proposing novel machine learning algorithms tend to present the algorithm or technique in question in the best possible light. The standard practice is generally for authors to emphasize their proposed algorithms' performance in the precise setting where it is maximally impressive, often by only fully evaluating their best known...
    Resource Type:
    Dissertation
    Full Text:
    Background We consider optimizing an unknown function f : X → R where X is a compact d- dimensional subset