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ReNAS:Relativistic Evaluation of Neural Architecture Search
Yixing Xu, Yunhe Wang, Kai Han +4
An effective and efficient architecture performance evaluation scheme is essential for the success of Neural Architecture Search (NAS). To save computational cost, most of existing…
Bringing Giant Neural Networks Down to Earth with Unlabeled Data
Yehui Tang, Shan You, Chang Xu +2
Compressing giant neural networks has gained much attention for their extensive applications on edge devices such as cellphones. During the compressing process, one of the most imp…
Evolutionary Generative Adversarial Networks
Chaoyue Wang, Chang Xu, Xin Yao +1
Generative adversarial networks (GAN) have been effective for learning generative models for real-world data. However, existing GANs (GAN and its variants) tend to suffer from trai…
A Survey on Multi-view Learning
Chang Xu, Dacheng Tao, Chao Xu
In recent years, a great many methods of learning from multi-view data by considering the diversity of different views have been proposed. These views may be obtained from multiple…