Showing 1 - 19 results of 19 for search '(( statistical modeling theory ) OR ( statistical learning theories ))~', query time: 0.16s Refine Results
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    Refining learning models in grammatical inference by Wang, Xiangrui

    Published 2008
    “…Grammatical inference is a branch of computational learning theory that attacks the problem of learning grammatical models from string samples. …”
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    Thesis
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    A reformulation of additive models by Wozniakowski, Alex

    Published 2022
    “…Additive models and their fitting algorithms play a pivotal role in the history and development of applied mathematics, machine learning, statistics, and science. …”
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    Thesis-Doctor of Philosophy
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    Integrated user-interface acceptance model for e-learning system by Ramadiani, -

    Published 2014
    “…Based on t-value, loading factors, and the relative suitability of each attribute, the User Interface Acceptance Model for e-learning can be accepted. Based on the Goodness of Fit statistical value in the first and the second model, the model of e-learning user interface has a highly significant correlation with e-learning acceptance. …”
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    Thesis
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    MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000 by Massachusetts Institute of Technology. Media Laboratory.

    Published 2000
    “…Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. …”
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    Learning Object
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    Topics in Bayesian machine learning for finance by Spears, T

    Published 2024
    “…We show a relevant, modern case of incorporating machine learning model-derived view and uncertainty estimates, and the impact on portfolio allocation, with an example subsuming Arbitrage Pricing Theory. …”
    Thesis
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    Theoretical study of spermatozoa sorting by dielectrophoresis or magnetophoresis with supervised learning by Koh, James Boon Yong

    Published 2019
    “…By fitting the model to a tenth of the sample size required for statistical convergence, predicted results are precise and accurate to a handful of percentage points. …”
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    Thesis
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    Bayes factors for logistic (mixed effect) models by Silvey, C, Dienes, Z, Wonnacott, E

    Published 2024
    “…Second, many implementations of Bayes factors have a substantial technical learning curve. We present a case study and simulations demonstrating a simple method for generating a range of plausible effect sizes, that is, a model of Hypothesis 1, for treatment effects where there is a binary-dependent variable. …”
    Journal article
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    Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications by Johnson, Nicholas André G.

    Published 2024
    “…This thesis advances both the theory and application of sparse and low rank matrix optimization, focusing on problems that arise in statistics and machine learning. …”
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    Thesis
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    Reliability analysis and data driven modelling of railway component failure by Wang, Jinlong

    Published 2022
    “…Such statistical models are under some distribution assumptions which may not be fully satisfied in practice, but the models can be fitted with limited data samples and their interpretabilities are high. …”
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    Thesis-Doctor of Philosophy
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    Modelling and characterization of membrane fouling in osmotically-driven membrane processes (ODMPs) by Lai, Li

    Published 2021
    “…The result is in agreement with ‘two-stage’ fouling theory, which is characterized by transition from particle-membrane interaction energy dominative system to particle-particle interaction energy dominative system. …”
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    Thesis-Doctor of Philosophy
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    Wireless channel modeling and spectrum monitoring for interference mitigation and link reliability insurance for existing and future CBTC systems by Kalyankar Shravan Kumar

    Published 2022
    “…Furthermore, the hand-crafted spectral signatures are replaced with the synthetic spectral signatures, and the identification of signals is performed using a deep learning algorithm. As a continuation to spectrum monitoring campaign, spectrum occupancy analysis, signal identification, a Gaussian Mixture Model (GMM) clustering technique is proposed to evaluate the performance of access points from identified CBTC signals when the train is stopped at the MRT station. …”
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    Thesis-Doctor of Philosophy
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    Numerical and Analytical Methods in Low-Dimensional Strongly Correlated Quantum Systems by Peng, Changnan

    Published 2024
    “…Furthermore, the thesis derives a Hamiltonian lattice formulation for the 2+1D compact Maxwell-Chern-Simons theory, providing an analytical solution that aligns with continuum theories and facilitating future numerical applications. …”
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    Thesis
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