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cs.DS2022
Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex Sets
Loay Mualem, Moran Feldman
In recent years, maximization of DR-submodular continuous functions became an important research field, with many real-worlds applications in the domains of machine learning, commu…
cs.LG2022★ 6 cited
Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions
Murad Tukan, Loay Mualem, Alaa Maalouf
Pruning is one of the predominant approaches for compressing deep neural networks (DNNs). Lately, coresets (provable data summarizations) were leveraged for pruning DNNs, adding th…
cs.LG2022★ 3 cited
Using Partial Monotonicity in Submodular Maximization
Loay Mualem, Moran Feldman
Over the last two decades, submodular function maximization has been the workhorse of many discrete optimization problems in machine learning applications. Traditionally, the study…