Machine Learning Meets Natural Language Processing -- The story so far

2021-03-27 · N. -I. Galanis, P. Vafiadis, K. -G. Mirzaev, G. A. Papakostas

Natural Language Processing (NLP) has evolved significantly over the last decade. This paper highlights the most important milestones of this period while trying to pinpoint the contribution of each individual model and algorithm to the overall progress. Furthermore, it focuses on issues still remaining to be solved, emphasizing the groundbreaking proposals of Transformers, BERT, and all the similar attention-based models.

📄 PDF Abstract BibTeX arXiv:2104.10213

Code (0)

등록된 구현이 없습니다.

Tasks

BIG-bench Machine Learning

Methods 이 논문이 사용한 방법론

Multi-Head Attention 설명 없음

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Refunds@Expedia|||How do I get a full refund from Expedia? “How do I get a full refund from Expedia? How do I get a full refund from Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Quick Help &…

Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…

Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

Attention 설명 없음

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.

Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism

2017-09-01 · WS 2017 9 ·

Federated Learning Meets Natural Language Processing: A Survey

2021-07-27 · Ming Liu, Stella Ho, Mengqi Wang, Longxiang Gao 외

Federated Learning aims to learn machine learning models from multiple decentralized edge devices (e.g. mobiles) or servers without sacrificing local data privacy. Recent Natural Language Processing techniques rely on de…

Federated Learning Survey

Natural Language Processing: State of The Art, Current Trends and Challenges

2017-08-17 · Diksha Khurana, Aditya Koli, Kiran Khatter, Sukhdev Singh

Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It has spread its applications in various fields such as machine translation, email spam…

Machine Translation Question Answering Spam detection Text Generation+1

When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning

2022-03-31 · Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer 외

Physics-informed machine learning (PIML), referring to the combination of prior knowledge of physics, which is the high level abstraction of natural phenomenons and human behaviours in the long history, with data-driven …

BIG-bench Machine Learning Physics-informed machine learning

Identifying Health Risks from Family History: A Survey of Natural Language Processing Techniques

2024-03-15 · Xiang Dai, Sarvnaz Karimi, Nathan O'Callaghan

Electronic health records include information on patients' status and medical history, which could cover the history of diseases and disorders that could be hereditary. One important use of family history information is …