4 citations · 12 across the 10 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.CV2023★ 1 cited
Poster: Self-Supervised Quantization-Aware Knowledge Distillation
Kaiqi Zhao, Ming Zhao
Quantization-aware training (QAT) starts with a pre-trained full-precision model and performs quantization during retraining. However, existing QAT works require supervision from t…
cs.LG2023★ 3 cited
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
Kaiqi Zhao, Animesh Jain, Ming Zhao
Pruning is a promising approach to compress deep learning models in order to deploy them on resource-constrained edge devices. However, many existing pruning solutions are based on…
cs.LG2023★ 1 cited
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning
Kaiqi Zhao, Yitao Chen, Ming Zhao
Knowledge Transfer (KT) achieves competitive performance and is widely used for image classification tasks in model compression and transfer learning. Existing KT works transfer th…