1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
TT-MPD: Test Time Model Pruning and Distillation
Haihang Wu, Wei Wang, Tamasha Malepathirana +3
Pruning can be an effective method of compressing large pre-trained models for inference speed acceleration. Previous pruning approaches rely on access to the original training dat…
cs.LG2024
When To Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks
Haihang Wu, Wei Wang, Tamasha Malepathirana +3
Neural growth is the process of growing a small neural network to a large network and has been utilized to accelerate the training of deep neural networks. One crucial aspect of ne…
cs.RO2023
Data-Driven Goal Recognition in Transhumeral Prostheses Using Process Mining Techniques
Zihang Su, Tianshi Yu, Nir Lipovetzky +6
A transhumeral prosthesis restores missing anatomical segments below the shoulder, including the hand. Active prostheses utilize real-valued, continuous sensor data to recognize pa…