1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2024
LLM-based Knowledge Pruning for Time Series Data Analytics on Edge-computing Devices
Ruibing Jin, Qing Xu, Min Wu +4
Limited by the scale and diversity of time series data, the neural networks trained on time series data often overfit and show unsatisfacotry performances. In comparison, large lan…
cs.LG2024
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Xue Geng, Zhe Wang, Chunyun Chen +10
Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI) tasks. However, deploying them brings significant challenges due to the huge cost of memory,…
cs.LG2024★ 1 cited
Improve Knowledge Distillation via Label Revision and Data Selection
Weichao Lan, Yiu-ming Cheung, Qing Xu +4
Knowledge distillation (KD) has become a widely used technique in the field of model compression, which aims to transfer knowledge from a large teacher model to a lightweight stude…