Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 6 of 6 for “"Dataset Selection"”.
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Hierarchical Bayesian Dataset Selection
… depends on access to large, high-quality datasets, which are often challenging to identify. To address this, we introduce <b>H</b>ierarchical <b>B</b>ayesian <b>D</b>ataset <b>S</b>election (<b>HBDS</b>), the first dataset selection algorithm that utilizes hierarchical Bayesian modeling, …
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Influence of training dataset selection on the performance of a machine learning model
… This work proposes to compose a good training dataset that would give good accuracy with a robust object detection model by using different training and testing combinations. Various evaluation techniques have been used in this work to check the impact of the training dataset, on the testing …
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Metagradient Descent: Differentiating Large-Scale Training
… descent (MGD), we greatly improve on existing dataset selection methods, outperform accuracy-degrading data poisoning attacks by an order of magnitude, and automatically find competitive learning rate schedules.
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How Data Drives ML Models Performance
… show the effectiveness of this approach in two dataset selection settings: language modeling and imitation learning. Second, we explore the role of data in model reliability and consider two different threat models: backdoor attacks and malicious data editing. In this first threat model, an …
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Symbolic and connectionist machine learning techniques for short-term electric load forecasting
… training database creation, training dataset selection, training data normalization are presented in context of nonlinear modeling in general and electric load forecasting in particular. Local function approximation and nearest neighbor norms techniques are applied to this task. …
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ADVANCED MACHINE LEARNING MODELS IN PREDICTION OF MEDICAL CONDITIONS
… understanding of disease pathogenesis makes the selection of an adequate ML model and accurate prediction more likely. The hypothesis of the research was to demonstrate that the optimal and adequate selection of model inputs as well as the selection and design of adequate ML methods improves the …