SOURCE-LINKED INTELLIGENCE

Multiclass Linear Perceptrons with Multiplicative Margins

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

This paper introduces a family of multiclass linear Perceptron classifiers with a multiplicative margin mechanism (MMPerc), as an alternative to standard margin-free and additive margin Perceptrons. The multiplicative formulation enforces classification confidence by requiring the true class score to exceed that of competing classes by a specified fraction of itself, rather than by a fixed additive threshold. This avoids dependence on score magnitudes arising from varied norms of data and class weight vectors. We propose several architectural and algorithmic variants of MMPerc, derive associat

Read original source ↗ Open in workspace

recordType: paper
region: Global

Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-08-30T20:32:04.000Z

First collected: 2026-09-21T07:22:03.933Z. This is not the publication date.