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Filtering by: Creator Sabin, Thomas E. Remove constraint Creator: Sabin, Thomas E. 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:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 5.3.4 E-step via Efficient Message Passing . . . . . . . . . . . . . . . . . 45 5.4 Prediction

  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation
    Full Text:
    information but also offers a plethora of potential applications, like augmented reality, e-commerce, and

  • 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:
    mentor. Thank you to Thomas Thüm, Paul Maximilian Bittner, and Tobias Heß. Tobias for supporting me

  • Variant Annotation

    Creator:
    He, Jun
    Abstract:
    With the development of technologies in genome sequencing and variant detection, a huge number of variants are detected. To further analyze the variants, it requires an efficient tool to annotate the functional effect of variants. This project managed to develop an efficient program to annotate the functional effect of variants...
    Resource Type:
    Capstone Project
    Full Text:
    format, http://www.ensembl.org/info/website/upload/gff.html 2016. [8] Charles E. Leiserson, Thomas H

  • Using RUBI to partition agents in air traffic problems with hard constraints and reward shaping

    Creator:
    Curran, William
    Abstract:
    Air traffic flow management over the U.S. airpsace is a difficult problem. Current management approaches lead to hundreds of thousands of hours of delay, costing billions of dollars annually. Weather and airport conditions may instigate this delay, but routing decisions balancing delay with congestion contribute significantly to the propagation of...
    Resource Type:
    Masters Thesis
    Full Text:
    problems arise as in the static environment [42]. In action-value learning agents enforce E-greedy

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation

  • Test case prioritization

    Creator:
    Malishevsky, Alexey Grigorievich
    Abstract:
    Regression testing is an expensive software engineering activity intended to provide confidence that modifications to a software system have not introduced faults. Test case prioritization techniques help to reduce regression testing cost by ordering test cases in a way that better achieves testing objectives. In this thesis, we are interested...
    Resource Type:
    Dissertation
    Full Text:
    : Test Case Prioritization. Abstract approved: Gregg E. Rothermel Regression testing is an expensive

  • 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
    Full Text:
    . Key Words: Genetic Algorithm, Crowdsourcing, Population Model Corresponding e-mail address: knowltjo

  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation

  • 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:
    domain 3: g(x0,0) = f(x0,0) 4: n = 1 5: loop 6: E = ∅ 7: vmax = −∞ 8: for h = 0 . . .min(depth (τ) , hmax