6 citations · 19 across the 27 of their papers we have counts for
4 papers · 1 filter
Exploring the Robustness of Decentralized Training for Large Language Models
Lin Lu, Chenxi Dai, Wangcheng Tao +3
Decentralized training of large language models has emerged as an effective way to democratize this technology. However, the potential threats associated with this approach have no…
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Peng Zeng, Xiaotian Song, Andrew Lensen +4
Symbolic regression (SR) is the process of discovering hidden relationships from data with mathematical expressions, which is considered an effective way to reach interpretable mac…
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence
Yuhao Zhou, Mingjia Shi, Yuanxi Li +3
Reducing communication overhead in federated learning (FL) is challenging but crucial for large-scale distributed privacy-preserving machine learning. While methods utilizing spars…
Differentiable Search of Accurate and Robust Architectures
Yuwei Ou, Xiangning Xie, Shangce Gao +3
Deep neural networks (DNNs) are found to be vulnerable to adversarial attacks, and various methods have been proposed for the defense. Among these methods, adversarial training has…