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 5 of 5 for “"hyperparameter search"”.
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Hyperparameter tuning and its effects on deep learning performance and generalization
Hyperparameter tuning is an integral part of deep learning research. Finding hyperparameter values that effectively leverage the strengths of network architectures and training procedures is crucial to maximizing performance. However, extensive hyperparameter searches raise concerns about …
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Data Driven Surrogate Models for Faster SPICE Simulation of Power Supply Circuits
… accuracy, but lacks practicality. This research implements a system to train surrogate models for an n-type MOSFET that can replace the nMOS device in SPICE simulation to improve performance while maintaining accuracy, regardless of the larger circuit context. We explore a variety of …
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Inductive logic programming with gradient descent for supervised binary classification
… Home Equity Line of Credit dataset. We run a hyperparameter search over differing number of rules and rule sizes. Our best performing model achieves a 71.7% accuracy, which is comparable to multilayer perceptron and randomized forest models. We conclude by suggesting directions for future …
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Evaluating, Understanding, and Mitigating Unfairness in Recommender Systems
… directly address the data biases. PRL poses the hyperparameter search problem as a secondary learning task. It enables back-propagation to learn the personalized regularization parameters by leveraging the closed-form solutions of alternating least squares (ALS) to solve MF. Furthermore, the …
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Efficient Multi-Objective NeuroEvolution in Computer Vision and Applications for Threat Identification
… endeavours to dis- cover and optimise models and hyperparameters autonomously, providing an alternative to classic, effort-intensive hyperparameter search. However, existing approaches typ- ically show significant downsides, like their (1) high computational cost/greediness in resources, (2) …