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cs.LG2026
Training deep physical neural networks with local physical information bottleneck
Hao Wang, Ziao Wang, Xiangpeng Liang +8
Deep learning has revolutionized modern society but faces growing energy and latency constraints. Deep physical neural networks (PNNs) are interconnected computing systems that dir…
cs.LG2025
Improving Pattern Recognition of Scheduling Anomalies through Structure-Aware and Semantically-Enhanced Graphs
Ning Lyu, Junjie Jiang, Lu Chang +3
This paper proposes a structure-aware driven scheduling graph modeling method to improve the accuracy and representation capability of anomaly identification in scheduling behavior…