Neural machine translation for low-resource languages: A survey
S Ranathunga, ESA Lee, M Prifti Skenduli… - ACM Computing …, 2023 - dl.acm.org
Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …
the early 2000s and has already entered a mature phase. While considered the most widely …
An overview of deep semi-supervised learning
Deep neural networks demonstrated their ability to provide remarkable performances on a
wide range of supervised learning tasks (eg, image classification) when trained on extensive …
wide range of supervised learning tasks (eg, image classification) when trained on extensive …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
S Bhattacharya, PKR Maddikunta, QV Pham… - Sustainable cities and …, 2021 - Elsevier
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
Self-training with noisy student improves imagenet classification
We present a simple self-training method that achieves 88.4% top-1 accuracy on ImageNet,
which is 2.0% better than the state-of-the-art model that requires 3.5 B weakly labeled …
which is 2.0% better than the state-of-the-art model that requires 3.5 B weakly labeled …
Unsupervised data augmentation for consistency training
Semi-supervised learning lately has shown much promise in improving deep learning
models when labeled data is scarce. Common among recent approaches is the use of …
models when labeled data is scarce. Common among recent approaches is the use of …
Survey of low-resource machine translation
We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …
research. There are currently around 7,000 languages spoken in the world and almost all …
Neural machine translation: A review
F Stahlberg - Journal of Artificial Intelligence Research, 2020 - jair.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …
natural language into another, has experienced a major paradigm shift in recent years …
An empirical survey of data augmentation for limited data learning in nlp
NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …
large labeled datasets. The dependence on abundant data prevents NLP models from being …
When and why are pre-trained word embeddings useful for neural machine translation?
The performance of Neural Machine Translation (NMT) systems often suffers in low-resource
scenarios where sufficiently large-scale parallel corpora cannot be obtained. Pre-trained …
scenarios where sufficiently large-scale parallel corpora cannot be obtained. Pre-trained …
Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …
decision strategies. However, in many cases, it is desirable to learn directly from …