2 papers
cs.LG2026
Exploiting Adaptive Channel Pruning for Communication-Efficient Split Learning
Jialei Tan, Zheng Lin, Xiangming Cai +4
Split learning (SL) transfers most of the training workload to the server, which alleviates computational burden on client devices. However, the transmission of intermediate featur…
cs.LG2024
Model Reprogramming Outperforms Fine-tuning on Out-of-distribution Data in Text-Image Encoders
Andrew Geng, Pin-Yu Chen
When evaluating the performance of a pre-trained model transferred to a downstream task, it is imperative to assess not only the in-distribution (ID) accuracy of the downstream mod…