自监督学习（Self-supervised Learning），笼统而言，是对于“损失函数中使用到的监督信息无需人工标注”的...
Self-supervised learning vs. unsupervised learning Self-supervised learning is a subset of unsupervised learning: all self-supervised learning techniques are unsupervised learning, but most unsupervised learning does not entail self-supervision. Neither unsupervised nor self-supervised learning use labels in...
自监督直接和具体任务的结合(Task Related Self-Supervised Learning)是个可探索的方向,已经在很多任务中初露头角,也比较符合审稿人的口味。 Reference [1]https://lawtomated.com/supervised-vs-unsupervised-learning-which-is-better/ [2]https://zhuanlan.zhihu.com/p/102573476 [3]https://zhuanlan.zhihu.com...
(正课)【生成式AI】Finetuning vs. Prompting:对于大型语言模型的不同期待所衍生的两类使用方式 (3_3) 15:34 (延申)自督导式学习 (Self-supervised Learning) (二) – BERT简介 50:41 (延申)自督导式学习 (Self-supervised Learning) (四) – GPT的野望 17:04 (作业)HW3 - CNN- Image Classifi...
This chapter discusses self-supervised and unsupervised learning approaches in deep learning. It covers clustering-based approaches, dimensionality reduction techniques, and recent advancements in self-supervised learning such as SimCLR, BYOL, and MoCo. Applications in computer vision, natural language ...
本来我的这篇分享是准备叫 「Self-Supervised Learning 入门介绍」,可惜在写作的过程中@Sherlock老哥抢先一步,所以只能叫「再次入门」了。 唉,这个时代,已经不仅仅是做科研需要手速了,在知乎写分享也要快 :( 本文通过整理自监督学习的一系列工作,把主流方法分成三大类,方便大家更全面的了解自监督学习的定义、方法、...
Semi-supervised Learning: 半监督学习,采用小部分人工打了标签的数据+大量的无标签的数据进行训练。 Weakly-supervised Learning:弱监督学习,训练用的数据标签通常是粗粒度的或者是不准确的标签。 Unsupervised Learning:无监督学习,指不用任何人工标签进行训练的方法。
We propose a self-supervised representation learning model for the task of unsupervised phoneme boundary detection. The model is a convolutional neural network that operates directly on the raw waveform. It is optimized to identify spectral changes in the signal using the Noise-Contrastive Estimation ...
machine-learningdeep-learningneural-networkdomain-driven-designneuroscienceeegeeg-signalsconvolutional-neural-networkstransfer-learningrepresentation-learningunsupervised-learningbiosignalsmulti-task-learningeeg-classificationself-supervisionself-supervised-learningelectroencephalogramelectrophysiological-dataml4hneurips-2021 ...
This paper explores the potential of self-supervised learning as an alternative to supervised learning in the context of geometry-based 3D object retrieval. With the ongoing digitalization of many industries, an exponentially increasing number of 3D objects are processed by retrieval systems. In order...