4 papers
Decision-Aware Quadratic ReLU Replacement for HE-Friendly Inference
Rui Li, Wenyuan Wu, Weijie Miao
Fully homomorphic encryption (FHE) supports only additions and multiplications, so FHE-only neural-network inference typically replaces ReLU with polynomials fitted over empirical…
Convex Dataset Valuation for Post-Training
Siqi Zeng, Christopher Jung, Rui Li +7
Improving LLM performance on downstream tasks sometimes requires leveraging auxiliary datasets during post-training. In practice, however, developers face constraints on compute, l…
HOSL: Hybrid-Order Split Learning for Memory-Constrained Edge Training
Aakriti Lnu, Zhe Li, Dandan Liang +3
Split learning (SL) enables collaborative training of large language models (LLMs) between resource-constrained edge devices and compute-rich servers by partitioning model computat…
Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach
Dandan Liang, Jianing Zhang, Evan Chen +3
Split Federated Learning (SFL) enables scalable training on edge devices by combining the parallelism of Federated Learning (FL) with the computational offloading of Split Learning…