8 citations · 12 across the 5 of their papers we have counts for
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cs.LG2023
Rotation Invariant Quantization for Model Compression
Joseph Kampeas, Yury Nahshan, Hanoch Kremer +4
Post-training Neural Network (NN) model compression is an attractive approach for deploying large, memory-consuming models on devices with limited memory resources. In this study,…
cs.LG2020★ 4 cited
Learning Branching Heuristics for Propositional Model Counting
Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu +4
Propositional model counting, or #SAT, is the problem of computing the number of satisfying assignments of a Boolean formula. Many problems from different application areas, includ…