Data augmentation and synthetic data generation are distinct yet complementary techniques in machine learning: Augmented data: This involves creating modified versions of existing data to increase dataset diversity. For example, in image processing, applying transformations like rotations, flips, or color ...
链接: What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspectivearxiv.org/abs/2012.02909 作者:Huan Wang, Suhas Lohit, Mike Jones, Yun Fu Affiliation:Northeastern University, Boston, MA; MERL, Cambridge, MA 本文已发表于 NeurIPS 2022。 本文讨论的是知识蒸馏当中...
2、Data Augmentation Methods in NLP 作者根据生成样本的多样性程度,将NLP中数据增强方法分为了以下三种: Paraphrasing:对句子中的词、短语、句子结构做一些更改,保留原始的语义。生成与原始数据语义差异有限的增强数据。增强的数据传递的信息与原始形式非常相似。 Noising:在保证label不变的同时,在文本上增加一些离散或...
1.2 Structure-wise Augmentation 分为四种方法: edge addition/dropping node addition/dropping graph diffusion graph sampling 1.2.1 Edge Addition/Dropping 即 保留原始节点顺序,对邻接矩阵种的元进行改写。 基于图稀疏性(graph sparsification)的图结构优化方法 [8、9],基于图结构整洁性(graph sanitation)的方法 [...
in machine learning models and CNN deep learning projects. It happens when the model learns the training data too well (“learning by heart”), including its noise and outliers. Such a learning leads to a model that performs well on the training data but badly on new, unseen data. ...
最近发现data augmentation已经有了一些理论工作,早一点的有ICML上的kernel theory。而今天要解读的是使用群理论进行分析的一篇文章。 摘要 数据增强在训练神经网络时被广泛使用:在训练集中除了原始数据还有被适度转换的数据。然而,据我们所知,用来解释数据增强的数学框架还没有出现。
2.1 Data Augmentations based on basic image manipulations 2.2 Geometric versus photometric transformations 2.3 Data Augmentations based on Deep Learning 3. Design considerations for image Data Augmentation C. Shorten and T. M. Khoshgoftaar, ‘A survey on Image Data Augmentation for Deep Learning’,...
Prototype Augmentation and Self-Supervision for Incremental Learning 2021 CVPR Class-incremental experience replay for continual learning under concept drift 2021 CVPRW Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning 2021 ICCV Using Hindsight to Anchor Past Knowledge in Continual...
SpecAugment是一种log梅尔声谱层面上的数据增强方法,可以将模型训练的过拟合问题转化为欠拟合问题,以便通过大网络和长时训练策略来缓解欠拟合问题,提升语音识别效果 模型: 输入特征:Fbank特征 声谱增强:将log梅尔声谱的时域和频域看作二维图像,时间片长度为τ,频域长度ν ...
Enterprise data warehouse development: definition, problems to solve, and real-life scenarios Enterprise data warehouse design was introduced by computer scientist B. Inmon and reveals his attitude to business data management. Let’s take Inmon’s definition of an EDW from his book “Building the ...