72 citations · 81 across the 6 of their papers we have counts for
6 papers
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Yong Guo, Yaofo Chen, Yin Zheng +5
Designing feasible and effective architectures under diverse computational budgets, incurred by different applications/devices, is essential for deploying deep models in real-world…
Automated Dominative Subspace Mining for Efficient Neural Architecture Search
Yaofo Chen, Yong Guo, Daihai Liao +4
Neural Architecture Search (NAS) aims to automatically find effective architectures within a predefined search space. However, the search space is often extremely large. As a resul…
Towards Lightweight Super-Resolution with Dual Regression Learning
Yong Guo, Mingkui Tan, Zeshuai Deng +5
Deep neural networks have exhibited remarkable performance in image super-resolution (SR) tasks by learning a mapping from low-resolution (LR) images to high-resolution (HR) images…
Content-Aware Convolutional Neural Networks
Yong Guo, Yaofo Chen, Mingkui Tan +3
Convolutional Neural Networks (CNNs) have achieved great success due to the powerful feature learning ability of convolution layers. Specifically, the standard convolution traverse…
AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu +5
In real-world applications, data often come in a growing manner, where the data volume and the number of classes may increase dynamically. This will bring a critical challenge for…
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Yong Guo, Yin Zheng, Mingkui Tan +4
Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically se…