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statistical learning » statistical modeling (Expand Search), statistical sampling (Expand Search)
statistical sharing » statistical sampling (Expand Search), statistical spatial (Expand Search), statistics spring (Expand Search)
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Statistics and Probability Theory : In Pursuit of Engineering Decision Support /
Published [201Get full text
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software, multimedia -
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18.217 Graph Theory and Additive Combinatorics, Fall 2019
Published 2024Get full text
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Combating China’s corruption through learning from Taobao’s business model.
Published 2013Get full text
Final Year Project (FYP) -
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Game theoretical, statistical and behavioural aspects of peer evaluation
Published 2021Get full text
Final Year Project (FYP) -
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Refining learning models in grammatical inference
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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MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000
Published 2000Subjects: “…machine and human learning…”
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Learning Object -
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Topics in Bayesian machine learning for finance
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. …”
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Macroeconomic and Firm-Specific Effects on Islamic Deposits Sustainability
Published 2024Get full text
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Theoretical study of spermatozoa sorting by dielectrophoresis or magnetophoresis with supervised learning
Published 2019“…The hydrodynamic force acting on the sperm is computed using Resistive Force Theory as well as Slender Body Theory, and the resulting velocity is compared qualitatively and quantitatively. …”
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Thesis -
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Integrated user-interface acceptance model for e-learning system
Published 2014“…As a learning process, e-learning is aimed to achieve learning objectives, through which, the education is expected to become more accessible, cheaper, more fun, and easier to share and to learn. …”
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Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications
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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A reformulation of additive models
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. Yet, the traditional methodology neglects the means to explicitly incorporate prior knowledge into the fit of an additive model, which is of great practical importance in regression tasks, especially in the low training example regime, where entirely data-driven learning is not always feasible. …”
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Thesis-Doctor of Philosophy