Model-parallel inference over dynamic edge systems requires scheduling decisions that account for not only instantaneous resources but also future resource contention and reliable service commitments. Existing edge-inference designs, however, predominantly optimize performance metrics based on current or short-term sys...
Minghui Liwang, Chen-Xi Xu, Wei Gong et al.· 0 citations
Muon is emerging as a promising alternative to AdamW for large-scale neural network training, yet theoretical understanding of its practical implementation remains incomplete, as existing analyses often simplify or omit two key components: (i) practical Newton--Schulz iterations with empirically tuned polynomial coeffi...
Hao-Nan Wang, Yu Wu, Minghui Liwang et al.· 0 citations
This paper studies 3D multi-UAV path planning and task assignment under uncertain ground PoI demands, and proposes FORTUNE, a hierarchical offline-online framework that consistently outperforms state-of-the-art methods in effectiveness, scalability, and practical applicability.
Minghui Liwang, Wen-Han Jia, Xin-Lei Yi et al.· 0 citations
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