4 citations · 5 across the 6 of their papers we have counts for
6 papers
DAS: Neural Architecture Search via Distinguishing Activation Score
Yuqiao Liu, Haipeng Li, Yanan Sun +1
Neural Architecture Search (NAS) is an automatic technique that can search for well-performed architectures for a specific task. Although NAS surpasses human-designed architecture…
Architecture Augmentation for Performance Predictor Based on Graph Isomorphism
Xiangning Xie, Yuqiao Liu, Yanan Sun +2
Neural Architecture Search (NAS) can automatically design architectures for deep neural networks (DNNs) and has become one of the hottest research topics in the current machine lea…
Evolving Deep Neural Networks for Collaborative Filtering
Yuhan Fang, Yuqiao Liu, Yanan Sun
Collaborative Filtering (CF) is widely used in recommender systems to model user-item interactions. With the great success of Deep Neural Networks (DNNs) in various fields, advance…
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search
Xiangning Xie, Yuqiao Liu, Yanan Sun +3
Neural architecture search (NAS), which automatically designs the architectures of deep neural networks, has achieved breakthrough success over many applications in the past few ye…
Homogeneous Architecture Augmentation for Neural Predictor
Yuqiao Liu, Yehui Tang, Yanan Sun
Neural Architecture Search (NAS) can automatically design well-performed architectures of Deep Neural Networks (DNNs) for the tasks at hand. However, one bottleneck of NAS is the p…
A Novel Training Protocol for Performance Predictors of Evolutionary Neural Architecture Search Algorithms
Yanan Sun, Xian Sun, Yuhan Fang +1
Evolutionary Neural Architecture Search (ENAS) can automatically design the architectures of Deep Neural Networks (DNNs) using evolutionary computation algorithms. However, most EN…