AI RESEARCH
Multiple Additive Neural Networks for Structured and Unstructured Data
arXiv CS.LG
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ArXi:2604.26888v1 Announce Type: new This paper extends and explains the Multiple Additive Neural Networks (MANN) methodology, an enhancement to the traditional Gradient Boosting framework, utilizing nearly shallow neural networks instead of decision trees as base learners. This innovative approach leverages neural network architectures, notably Convolutional Neural Networks (CNNs) and Capsule Neural Networks, to extend its application to both structured data and unstructured data such as images and audio.