Deep Learning 2.0: Extending the Power of Deep Learning to the Meta-Level

Deep Learning 2.0: Extending the Power of Deep Learning to the Meta-Level

Deep Learning 2.0: Extending the Power of Deep Learning to the Meta-Level Author: Frank Hutter https://www.automl.org/author/fhutter/ Deep learning has been able to revolutionize learning from raw data (images, text, speech, etc.) by replacing handcrafted features from specific domains with features learned jointly for the specific task at hand. In this blog post, I propose to … Read more

Few-Shot NER with Dual-Tower BERT Model

Few-Shot NER with Dual-Tower BERT Model

Delivering NLP technical insights to you every day! Author | SinGaln Source | PaperWeekly This is an article from ACL 2022. The overall idea is to use a dual-tower BERT model to encode text tokens and their corresponding labels separately based on meta-learning, and then perform classification on the output obtained from the dot product … Read more

ACL2022 | Dual Tower BERT Model with Label Semantics

ACL2022 | Dual Tower BERT Model with Label Semantics

Delivering NLP technology insights to you every day! Source: Alchemy Notes Author: SinGaln This is a paper from ACL 2022. The overall idea is to use a dual tower BERT model based on meta-learning to encode text tokens and their corresponding labels separately, and then perform a classification task using the output obtained from their … Read more

Meta-Learning: The Future of Machine Learning

Meta-Learning: The Future of Machine Learning

1 Introduction to Algorithms Meta-learning, also known as “learning how to learn,” is an exciting and highly promising research direction in the field of machine learning. Traditional machine learning algorithms typically require a large amount of data to train models, and when the data distribution changes or a new task is encountered, the model often … Read more

New Method for Self-Correcting Neural Networks

New Method for Self-Correcting Neural Networks

Originally published by Data Practitioners The process of neural networks includes the updating of its weight matrix (Weight Matrix: WM). Once the network training is complete, the weight matrix will be permanently fixed, and its effectiveness is evaluated based on the network’s generalization results on the test data. However, many environments continue to evolve after … Read more

Not Just BERT! Top 10 Exciting Ideas in NLP for 2018

Not Just BERT! Top 10 Exciting Ideas in NLP for 2018

Author: Sebastian Ruder, Translated by QbitAI 2018 was a significant year for the field of NLP. The most notable was BERT, which swept various NLP tests and was hailed as the beginning of a new era in NLP. But in 2018, there was more than just BERT. Recently, Irish NLP researcher Sebastian Ruder wrote an … Read more