Algorithms for the Training of Neural Support Vector Machines
arXiv:2308.07204v13 citationsh-index: 6
Originality Synthesis-oriented
AI Analysis
This work addresses the training of NSVMs, which incorporate domain knowledge into model design, but it appears incremental as it adapts existing methods without broad SOTA claims.
The authors tackled the problem of training neural support vector machines (NSVMs) by introducing algorithms based on the Pegasos algorithm, and they demonstrated their approach by solving standard machine learning tasks as a proof of concept.
Neural support vector machines (NSVMs) allow for the incorporation of domain knowledge in the design of the model architecture. In this article we introduce a set of training algorithms for NSVMs that leverage the Pegasos algorithm and provide a proof of concept by solving a set of standard machine learning tasks.