Cross-Entropy
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Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article