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IEEE transactions on neural networks and learning systems
Oct 5, 2022
In recommendation, both stationary and dynamic user preferences on items are embedded in the interactions between users and items (e.g., rating or clicking) within their contexts. Sequential recommender systems (SRSs) need to jointly involve such con...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
Spike-timing-dependent plasticity (STDP) is one of the most popular and deeply biologically motivated forms of unsupervised Hebbian-type learning. In this article, we propose a variant of STDP extended by an additional activation-dependent scale fact...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Spiking neural networks (SNNs) have shown clear advantages over traditional artificial neural networks (ANNs) for low latency and high computational efficiency, due to their event-driven nature and sparse communication. However, the training of deep ...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Pretrained deep models hold their learnt knowledge in the form of model parameters. These parameters act as "memory" for the trained models and help them generalize well on unseen data. However, in absence of training data, the utility of a trained m...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Driven by the outstanding performance of neural networks in the structured euclidean domain, recent years have seen a surge of interest in developing neural networks for graphs and data supported on graphs. The graph is leveraged at each layer of the...
Sensors (Basel, Switzerland)
Oct 4, 2022
Rotating machinery plays an important role in industrial systems, and faults in the machinery may damage the system health. A novel image-based diagnosis method using improved deep convolutional generative adversarial networks (DCGAN) is proposed for...
PloS one
Oct 4, 2022
Owing to the development of computerized vision technology, object detection based on convolutional neural networks is being widely used in the field of bridge crack detection. However, these networks have limited utility in bridge crack detection be...
Nature communications
Oct 2, 2022
Learning is a fundamental component of creating intelligent machines. Biological intelligence orchestrates synaptic and neuronal learning at multiple time scales to self-organize populations of neurons for solving complex tasks. Inspired by this, we ...
Computational intelligence and neuroscience
Sep 30, 2022
Today, English is the world's main international language and is widely spoken. In this context, the learning of English has long been valued by all countries. In addition, English plays an essential role in the process of economic globalization, spe...
Computational intelligence and neuroscience
Sep 28, 2022
Despite the emergence of various human-robot collaboration frameworks, most are not sufficiently flexible to adapt to users with different habits. In this article, a Multimodal Reinforcement Learning Human-Robot Collaboration (MRLC) framework is prop...