Toward the third generation artificial intelligence

B Zhang, J Zhu, H Su - Science China Information Sciences, 2023‏ - Springer
There have been two competing paradigms in artificial intelligence (AI) development ever
since its birth in 1956, ie, symbolism and connectionism (or sub-symbolism). While …

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

W Li, R Huang, J Li, Y Liao, Z Chen, G He… - … Systems and Signal …, 2022‏ - Elsevier
Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …

Applications of artificial intelligence in dentistry: A comprehensive review

F Carrillo‐Perez, OE Pecho, JC Morales… - Journal of Esthetic …, 2022‏ - Wiley Online Library
Objective To perform a comprehensive review of the use of artificial intelligence (AI) and
machine learning (ML) in dentistry, providing the community with a broad insight on the …

Transfer learning promotes 6G wireless communications: Recent advances and future challenges

M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021‏ - ieeexplore.ieee.org
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …

A survey of zero-shot learning: Settings, methods, and applications

W Wang, VW Zheng, H Yu, C Miao - ACM Transactions on Intelligent …, 2019‏ - dl.acm.org
Most machine-learning methods focus on classifying instances whose classes have already
been seen in training. In practice, many applications require classifying instances whose …

Neural unsupervised domain adaptation in NLP---a survey

A Ramponi, B Plank - arxiv preprint arxiv:2006.00632, 2020‏ - arxiv.org
Deep neural networks excel at learning from labeled data and achieve state-of-the-art
resultson a wide array of Natural Language Processing tasks. In contrast, learning from …

A survey on negative transfer

W Zhang, L Deng, L Zhang, D Wu - IEEE/CAA Journal of …, 2022‏ - ieeexplore.ieee.org
Transfer learning (TL) utilizes data or knowledge from one or more source domains to
facilitate learning in a target domain. It is particularly useful when the target domain has very …

A survey on multi-task learning

Y Zhang, Q Yang - IEEE transactions on knowledge and data …, 2021‏ - ieeexplore.ieee.org
Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to
leverage useful information contained in multiple related tasks to help improve the …

A survey of evolutionary algorithms for multi-objective optimization problems with irregular Pareto fronts

Y Hua, Q Liu, K Hao, Y ** - IEEE/CAA Journal of Automatica …, 2021‏ - ieeexplore.ieee.org
Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …

Challenges and opportunities beyond structured data in analysis of electronic health records

M Tayefi, P Ngo, T Chomutare… - Wiley …, 2021‏ - Wiley Online Library
Electronic health records (EHR) contain a lot of valuable information about individual
patients and the whole population. Besides structured data, unstructured data in EHRs can …