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pro vyhledávání: '"Adde, Nihal Acharya"'
This paper focuses on hyperparameter optimization for autonomous driving strategies based on Reinforcement Learning. We provide a detailed description of training the RL agent in a simulation environment. Subsequently, we employ Efficient Global Opti
Externí odkaz:
http://arxiv.org/abs/2407.14262
The logcosh loss function for neural networks has been developed to combine the advantage of the absolute error loss function of not overweighting outliers with the advantage of the mean square error of continuous derivative near the mean, which make
Externí odkaz:
http://arxiv.org/abs/2101.10427
Autor:
Adde, Nihal Acharya, Moshagen, Thilo
In the case of clustered data, an artificial neural network with logcosh loss function learns the bigger cluster rather than the mean of the two. Even more so, the ANN when used for regression of a set-valued function, will learn a value close to one
Externí odkaz:
http://arxiv.org/abs/2011.07332