32 citations · 46 across the 5 of their papers we have counts for
5 papers
Privacy-preserving Online AutoML for Domain-Specific Face Detection
Chenqian Yan, Yuge Zhang, Quanlu Zhang +4
Despite the impressive progress of general face detection, the tuning of hyper-parameters and architectures is still critical for the performance of a domain-specific face detector…
Learning to Rank Ace Neural Architectures via Normalized Discounted Cumulative Gain
Yuge Zhang, Quanlu Zhang, Li Lyna Zhang +4
One of the key challenges in Neural Architecture Search (NAS) is to efficiently rank the performances of architectures. The mainstream assessment of performance rankers uses rankin…
PAMS: Quantized Super-Resolution via Parameterized Max Scale
Huixia Li, Chenqian Yan, Shaohui Lin +5
Deep convolutional neural networks (DCNNs) have shown dominant performance in the task of super-resolution (SR). However, their heavy memory cost and computation overhead significa…
Interpretable Neural Network Decoupling
Yuchao Li, Rongrong Ji, Shaohui Lin +5
The remarkable performance of convolutional neural networks (CNNs) is entangled with their huge number of uninterpretable parameters, which has become the bottleneck limiting the e…
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Shaohui Lin, Rongrong Ji, Chenqian Yan +5
Structured pruning of filters or neurons has received increased focus for compressing convolutional neural networks. Most existing methods rely on multi-stage optimizations in a la…