Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. (arXiv:2206.08496v1 [cs.LG])

Web: http://arxiv.org/abs/2206.08496

Pre-training on time series poses a unique challenge due to the potential
mismatch between pre-training and target domains, such as shifts in temporal
dynamics, fast-evolving trends, and long-range and short cyclic effects, which
can lead to poor downstream performance. While domain adaptation methods can
mitigate these shifts, most methods need examples directly from the target
domain, making them suboptimal for pre-training. To address this challenge,
methods need to accommodate target domains with different temporal dynamics and
be capable of doing …

arxiv lg pre-training time time series training