Semi-Supervised Learning
التعلم شبه المُوجَّه
نمط هجين يدرب النموذج على كمية صغيرة من البيانات المُعلمة مدعومة بكميات هائلة من المعطيات الحرة.
A hybrid pattern training the model on a small amount of labeled data supported by large amounts of unlabeled data.
Also translated asالتعلم الهجين الموجه جزئياً، الحوسبة المختلطة بين البيانات الـمُعلمة والحرة، الحوسبة المختلطة بين البيانات المُعلمة والحرة
First appears in this corpus in: Representation Learning: A Review and New Perspectives (2013)
Appears in these papers
- Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning2020in the sky ✦
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data2024in the sky ✦
- Semi-Supervised Classification with Graph Convolutional Networks2017in the sky ✦
- Semi-Supervised Classification with Graph Convolutional Networks2017in the sky ✦
- Representation Learning: A Review and New Perspectives2013in the sky ✦
- Unsupervised Representation Learning by Predicting Image Rotations2018in the sky ✦
- Unsupervised Representation Learning by Predicting Image Rotations2018in the sky ✦
- A Simple Framework for Contrastive Learning of Visual Representations2020in the sky ✦
- Universal Language Model Fine-Tuning for Text Classification2018in the sky ✦
- Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision2023in the sky ✦
- Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision2023in the sky ✦