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Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions
PulseAugur coverage of Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions — every cluster mentioning Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions across labs, papers, and developer communities, ranked by signal.
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New VPOS method offers faster, more accurate feature selection
Researchers have introduced Variance-Preserving Orthogonal Selection (VPOS), a novel greedy framework for unsupervised feature selection. VPOS operates within the weighted PCA loading space and uses null-space deflation…
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New method advances neural set function learning, reducing computational overhead
Researchers have developed a new method to improve the learning of neural set functions, which are crucial for applications like drug discovery and product recommendation. The approach reinterprets the evidence lower bo…