An LP-based hyperparameter optimization model for language modeling
@article{Rahnama2018AnLH,
title={An LP-based hyperparameter optimization model for language modeling},
author={Amir Hossein Akhavan Rahnama and M. Toloo and N. Zaidenberg},
journal={The Journal of Supercomputing},
year={2018},
volume={74},
pages={2151-2160}
}In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models’ hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to… CONTINUE READING
2 Citations
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