2 papers
cs.LG2026
CRISP: Co-designing Pruning and Scheduling for Efficient MoE Inference on Edge Servers
Congwei Zhang, Youming Tao, Yifei Zou +6
Mixture-of-Experts (MoE) inference on memory-constrained edge platforms is often dominated by expert-weight movement rather than computation. Although each token activates only a s…
cs.LG2023
Adaptive pruning-based Newton's method for distributed learning
Shuzhen Chen, Yuan Yuan, Youming Tao +3
Newton's method leverages curvature information to boost performance, and thus outperforms first-order methods for distributed learning problems. However, Newton's method is not pr…