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View all- Wang MZhang CSong J(2024)CrowdDC: Ranking From Crowdsourced Paired Comparison With Divide-and-ConquerIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.329663211:2(3015-3021)Online publication date: Apr-2024
Many problems of substantial current interest in machine learning, statistics, and data science can be formulated as sparse and low-rank optimization problems. In this paper, we present the nonconvex exterior-point optimization solver (NExOS)—a ...
A method for ranking of alternatives or objects and its extensions by incomplete pairwise comparisons using random set theory are proposed in the paper. The main feature of the method is that it allows us to deal with comparisons of arbitrary groups of ...
Low-rank inducing unitarily invariant norms have been introduced to convexify problems with a low-rank/sparsity constraint. The most well-known member of this family is the so-called nuclear norm. To solve optimization problems involving such ...
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