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Toward the third generation artificial intelligence
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 …
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
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 …
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
Applications of artificial intelligence in dentistry: A comprehensive review
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 …
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
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …
accuracy, energy efficiency, and many other key performance indicator requirements are …
A survey of zero-shot learning: Settings, methods, and applications
Most machine-learning methods focus on classifying instances whose classes have already
been seen in training. In practice, many applications require classifying instances whose …
been seen in training. In practice, many applications require classifying instances whose …
Neural unsupervised domain adaptation in NLP---a survey
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 …
resultson a wide array of Natural Language Processing tasks. In contrast, learning from …
A survey on negative transfer
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 …
facilitate learning in a target domain. It is particularly useful when the target domain has very …
A survey on multi-task learning
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 …
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
Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …
optimization problems (MOPs). However, their performance often deteriorates when solving …
Challenges and opportunities beyond structured data in analysis of electronic health records
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 …
patients and the whole population. Besides structured data, unstructured data in EHRs can …