Large-scale sparse multi-objective optimization problems are prevalent in numerous real-world scenarios, such as neural network training, sparse regression, pattern mining and critical node detection, ...
Science and engineering problems in real world includes multiple conflicting objectives required to be optimized and are called multi-objective optimization Problems (MooPs). The aim is to minimize or ...
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