AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results show that even with appropriate biases and near-perfect OOD accuracy, a model can fail to learn the compositional feature structures necessary for systematic generalisation, indicating that OOD benchmarks alone are insufficient for evaluating compositionality in neural networks.
The dominance of Neural Networks (NNs) in RL is partially due to their incremental learning capability, which naturally suits the online, non-stationary nature of self-play training. However, gradient-boosted trees like LightGBM are widely recognised as the state of the art for tabular data in supervised learning, ofte...
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