English(EN) Contrastive Order Learning: A General Framework for Ordinal Regression

对比序数学习框架增强序数回归任务

作者 PulseAugur 编辑部 · [3 个来源] · 2026-07-09 04:48

研究人员引入了对比序数学习（ConOrd），一个结合了对比学习和序数学习用于序数回归任务的新颖框架。该方法旨在通过在批次内所有样本对之间实现序数关系的细粒度建模来利用这两种方法的优势。ConOrd在涉及面部年龄估计、盲图像质量评估和盲视频质量评估的实验中展示了最先进的性能。 AI

影响为序数回归任务引入了一种新方法，有望提高年龄估计和质量评估等应用中的性能。

排序理由该集群包含一篇详细介绍新机器学习框架的学术论文。

AI 生成摘要 · Google Gemini · 来自 3 个来源。我们如何撰写摘要 →

报道来源 [3]

arXiv cs.LG TIER_1 English(EN) · Chaewon Lee, BeomJun Shim, Kwang Pyo Choi, Chang-Su Kim · 2026-07-10 04:00

Contrastive Order Learning: A General Framework for Ordinal Regression

arXiv:2607.08109v1 Announce Type: new Abstract: We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. While contrastive learning effectively leverages all s…
arXiv cs.LG TIER_1 English(EN) · Chang-Su Kim · 2026-07-09 04:48

Contrastive Order Learning: A General Framework for Ordinal Regression

We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. While contrastive learning effectively leverages all samples in a batch, it typically ignores the inhe…
Hugging Face Daily Papers TIER_1 English(EN) · 2026-07-09 04:48

Contrastive Order Learning: A General Framework for Ordinal Regression

We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. While contrastive learning effectively leverages all samples in a batch, it typically ignores the inhe…