https://github.com/noise-learning/SelfMix/blob/maingithub.com/noise-learning/SelfMix/blob/main 一、概述 在工业界的很多实际任务中,都难免会遇到数据中存在噪音的情况。虽然这几年大型预训练模型的出现,让噪音数据的影响没那么大了。但是噪音样本比例大于一定情况的时候,大模型也会受到影响。目前解决噪音样...
Noise-robust dictionary learningSlack block-diagonal structureStrict '0-1' block-diagonal structure has been widely used for learning structured representation in face recognition problems. However, it is questionable and unreasonable to assume the within-class representations are the same. To circumvent ...
大模型(LLM)最新论文摘要 | Software Entity Recognition with Noise-Robust Learning Authors: Tai Nguyen, Yifeng Di, Joohan Lee, Muhao Chen, Tianyi Zhang Recognizing software entities such as library names from free-form text is essential to enable many software engineering (SE) technologies, such as...
The exemplified methods and systems facilitate the training of a noise-robust deep learning network that is sufficiently robust in the recognition of objects in images having extremely noisy elements such that the noise-robust network can match, or exceed, the performance of human counterparts. The ...
master 1Branch0Tags Code This branch is15 commits ahead of,2 commits behindLiJiaBei-7/nrccr:master. README License Cross-Lingual Cross-Modal Retrieval with Noise-Robust Learning source code of our paperCross-Lingual Cross-Modal Retrieval with Noise-Robust Learning ...
We compute the derivativeof this criterion using the chain rule and optimize it using stochastic gradient descent.In the second part, we introduce a new learning rule for neural networks that is based onan auxiliary function technique without parameter tuning. Instead of minimizing the objective...
A challenging, unsolved problem in the speech recognition community is recognizing speech signals that are corrupted by loud, highly nonstationary noise. One approach to noisy speech recognition is to automatically remove the noise from the cepstrum sequence before feeding ...
Quantum learning robust against noise Physical Review A - AMODownload paperAbstract Noise is often regarded as anathema to quantum computation, but in some settings it can be an unlikely ally. We consider the problem of learning the class of n-bit parity functions by making queries to a quantum...
AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong clas... Q Miao,C Ying,X Ge,... - 《IEEE Transactions on Neural Networks & Learning Systems》 被引量: 18发表: 2017年 ieee transactions on neura...
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss /LDAM 论文解读 1.LDMA介绍 一般来说,同一类别样本的特征在特征空间上的距离是比较接近的,不同类别样本的特征在特征空间上距离是比较远的。于是分类问题本质上是在找一条决策边界,使这些特征点能被正确… adward6 Meta开发System 2蒸馏技术,Ll...