Multi-Task Multicriteria Hyperparameter Optimization

Kirill Akhmetzyanov, Alexander Yuzhakov

Keywords: hyperparameter optimization, machine learning, neural network

Abstract: We present a new method for searching optimal hyperparameters among several tasks and several criteria. Multi-Task Multi Criteria method (MTMC) provides several Pareto-optimal solutions, among which one solution is selected with given criteria significance coefficients. The article begins with a mathematical formulation of the problem of choosing optimal hyperparameters. Then, the steps of the MTMC method that solves this problem are described. The proposed method is evaluated on the image classification problem using a convolutional neural network. The article presents optimal hyperparameters for various criteria significance coefficients.

One-sentence Summary: Pareto-based hyperparametric optimization method on several tasls with criteria significance coefficients

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