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cs.LG2025
Trustworthy Efficient Communication for Distributed Learning using LQ-SGD Algorithm
Hongyang Li, Lincen Bai, Caesar Wu +3
We propose LQ-SGD (Low-Rank Quantized Stochastic Gradient Descent), an efficient communication gradient compression algorithm designed for distributed training. LQ-SGD further deve…
cs.LG2025★ 1 cited
A Unified Hyperparameter Optimization Pipeline for Transformer-Based Time Series Forecasting Models
Jingjing Xu, Caesar Wu, Yuan-Fang Li +2
Transformer-based models for time series forecasting (TSF) have attracted significant attention in recent years due to their effectiveness and versatility. However, these models of…
cs.LG2024
Trustworthiness of Stochastic Gradient Descent in Distributed Learning
Hongyang Li, Caesar Wu, Mohammed Chadli +2
Distributed learning (DL) uses multiple nodes to accelerate training, enabling efficient optimization of large-scale models. Stochastic Gradient Descent (SGD), a key optimization a…