21 citations · 96 across the 32 of their papers we have counts for
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cs.LG2026
Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection
Mathieu Cherpitel, Thomas Bäck, Martijn R. Tannemaat +1
Unsupervised feature selection is commonly formulated as a multiobjective optimisation problem that jointly optimises subset quality and subset size. Yet the behaviour of this form…
cs.LG2026
Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives
Wei Liu, Yaoxin Wu, Yingqian Zhang +2
Deep reinforcement learning (DRL) has shown great promise in addressing multi-objective combinatorial optimization problems (MOCOPs). Nevertheless, the robustness of these learning…