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  • A General Purpose Agent-Based Blackboard Optimization Method Applied to Sodium Fast Reactor Design and Analysis

    Creator:
    Stewart, Ryan H.
    Abstract:
    We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
    Resource Type:
    Dissertation

  • Nonuniform Sampling Of Band-limited Functions

    Creator:
    Al-Hammali, Hussain Y.
    Abstract:
    In this thesis, we will study certain generalizations of the classical Shannon Sampling Theorem, which allows for the reconstruction of a pi-band-limited, square-integrable function from its samples on the integers. J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which includes nonuniform and...
    Resource Type:
    Dissertation
    Full Text:
    . A function f is in the Paley-Wiener space PWp ⇡ , 1  p  1 if f(z) = R ⇡ �⇡ g(w)e izwdw, z 2 C

  • Representationally Robust and Scalable Learning over Relational Databases

    Creator:
    Picado Leiva, Jose Manuel
    Abstract:
    Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
    Resource Type:
    Dissertation
    Full Text:
    schema: advisedBy(x, y)←inPhase(x, ‘post quals’), ta(v, x, w), taughtBy(v, y, z). 10 Original Schema

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    ), exhibit trends with window size w consistent with the distribution of distances observed in CompaRNA-1m

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation
    Full Text:
    biological neurons. Usually, in neural networks the goal is to learn a set of wight matrices W s and bias

  • 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:
    nearest half-hour, and records are presented as [W, L D]. Tables G.1–G.4 all will use a similar format

  • 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
    Full Text:
    modeled by some statistical model with parameters w. So F can also be written as Fw. This problem is

  • Improving the Effectiveness of Answering Keyword Queries Using Effective Subsets

    Creator:
    Khodadadi, Abtin
    Abstract:
    Most database users do not know formal query languages, such as SQL, and prefer to express their information needs using usable query languages, such as keyword queries. Keyword queries, however, are inherently ambiguous and challenging for the database systems to understand and answer effectively. We propose a novel approach to...
    Resource Type:
    Capstone Project
    Full Text:
    tuple t ∈ I, we denote the popularity of t as w(t). The sequence of the subsets has the following

  • Reinforcement learning for job-shop scheduling

    Creator:
    Zhang, Wei, 1960-
    Resource Type:
    Dissertation
    Full Text:
    Samual's checker-playing program [Samuel, 1959] and the LEX system [Mitchell et al., 1983]. Applying

  • 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