1.1k citations · 1.7k across the 22 of their papers we have counts for
3 papers · 1 filter
A Survey of Deep Active Learning
Pengzhen Ren, Yun Xiao, Xiaojun Chang +5
Active learning (AL) attempts to maximize the performance gain of the model by marking the fewest samples. Deep learning (DL) is greedy for data and requires a large amount of data…
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
Pengzhen Ren, Yun Xiao, Xiaojun Chang +4
Deep learning has made breakthroughs and substantial in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is…
RWR-GAE: Random Walk Regularization for Graph Auto Encoders
Vaibhav, Po-Yao Huang, Robert Frederking
Node embeddings have become an ubiquitous technique for representing graph data in a low dimensional space. Graph autoencoders, as one of the widely adapted deep models, have been…