11 citations · 12 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 11 cited
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
Haozhi Gao, Qianqian Ren, Jinbao Li
Contrastive representation learning is crucial in time series analysis as it alleviates the issue of data noise and incompleteness as well as sparsity of supervision signal. Howeve…
stat.ML2019★ 1 cited
Global Momentum Compression for Sparse Communication in Distributed Learning
Chang-Wei Shi, Shen-Yi Zhao, Yin-Peng Xie +2
With the rapid growth of data, distributed momentum stochastic gradient descent~(DMSGD) has been widely used in distributed learning, especially for training large-scale deep model…