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The experiment results shows that the classification results of BPAEPML is similar to that of the traditional BP neural network multi-label classification ...
Algorithm Based on Approximate Extreme Points. Xupeng Wang+, Zhongwen Guo+ ... provides a point cut for fast multi-label classification to other multi ...
This chapter presents a decades-old, extremely powerful classification algorithm that can be cast in the form of a neural network. Learning speed for this model ...
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Oct 18, 2017 · To solve this problem, this paper provides a fast multi-label SVM classification algorithm based on approximate extreme points (AEMLSVM).
Fast Multi-Label Low-Rank Linearized SVM Classification Algorithm Based on Approximate Extreme Points · Computer Science. IEEE Access · 2018.
A Fast Neural Network Multi-label Classification Algorithm Based on Approximate Extreme Points. Xupeng Wang, Zhongwen Guo, Xi Wang, Mengdi Min, Yangfan Zhao.
Apr 20, 2023 · c) Embedding based methods: These methods rely on low-dimensional embeddings to approximate the label space. Examples include AnnexML [20] and ...
Extreme multi-label classification (XMC) is the problem of finding the relevant labels for an in- put, from a very large universe of possible labels.
Aug 24, 2024 · In this paper, we propose Gandalf, a novel approach which makes use of a label co-occurrence graph to leverage label features as additional data points.
An Efficient Multi-Label SVM Classification Algorithm by Combining Approximate Extreme Points Method and Divide-and-Conquer Strategy · Figures and Tables · Topics ...