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Found 3 papers, 1 papers with code
ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY
We study the problem of using low cost to search for hyperparameter configurations in a large search space with heterogeneous evaluation cost and model quality.
Frugal Optimization for Cost-related Hyperparameters
To address this problem, we develop a new cost-frugal HPO solution.
ABC: Efficient Selection of Machine Learning Configuration on Large Dataset
A machine learning configuration refers to a combination of preprocessor, learner, and hyperparameters.
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