Optimizing the Hyperparameter Tuning of YOLOv5 for Underwater Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3174583
Abstract: This study optimized the latest YOLOv5 framework, including its subset models, with training on different datasets that differed in image contrast and cloudiness to assess model performances based on quantitative metrics and image processing speed.… read more here.
Keywords: optimizing hyperparameter; hyperparameter tuning; learning rate; hyperparameter ... See more keywords
Automatic Hyperparameter Tuning in Sparse Matrix Factorization
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DOI: 10.1162/neco_a_01581
Abstract: Abstract We study the problem of hyperparameter tuning in sparse matrix factorization under a Bayesian framework. In prior work, an analytical solution of sparse matrix factorization with Laplace prior was obtained by a variational Bayes… read more here.
Keywords: matrix factorization; sparse matrix; hyperparameter tuning; matrix ... See more keywords
High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms
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DOI: 10.48550/arxiv.2207.06028
Abstract: Hyperparameters in machine learning (ML) have received a fair amount of attention, and hyperparameter tuning has come to be regarded as an important step in the ML pipeline. However, just how useful is said tuning?… read more here.
Keywords: hyperparameter; hyperparameter tuning; large scale; machine learning ... See more keywords