Feb. 16, 2024, 5:41 a.m. | Xiaoyuan Zhang, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.09486v1 Announce Type: new
Abstract: Multiobjective optimization (MOO) is prevalent in numerous applications, in which a Pareto front (PF) is constructed to display optima under various preferences. Previous methods commonly utilize the set of Pareto objectives (particles on the PF) to represent the entire PF. However, the empirical distribution of the Pareto objectives on the PF is rarely studied, which implicitly impedes the generation of diverse and representative Pareto objectives in previous methods. To bridge the gap, we suggest in …

abstract algorithm applications arxiv cs.lg optimization pareto set type uniform

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