River monitoring stations record multiple hydro-environmental variables over a common river-network topology. While their sampling frequencies and temporal dynamics differ substantially, shared riverine drivers imply that densely observed hydrological variables can inform sparsely sampled water-quality targets; the pra...
Yaotian Zhu, Ruiyao Xu, Zhaoyang Guan et al.· Proceedings of the 32nd ACM...· 0 citations
Modern machine learning techniques, particularly deep learning, have shown remarkable efficacy in numerous knowledge discovery and data mining applications. However, the advancement of these methods is frequently impeded by resource constraint challenges in many scenarios, such as limited labeled data (data-level), sma...
Chu-Xu Zhang, Kai-Ze Ding, D. Xu et al.· Proceedings of the 32nd ACM...· 0 citations
GroupMask is proposed, which generates the group selectors of all layers with a lightweight hypernetwork, relaxes them with a Gumbel-Sigmoid parameterization and a straight-through estimator, and learns them through sparsity-budget regularization and self-distillation while keeping the pretrained weights frozen.
Zhen-Gao Li, Shuo-Qiu Li, Xiao-Fan Zhang et al.· 0 citations
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