Surrogate models have shown to be effective in assisting evolutionary algorithms (EAs) for solving computationally expensive complex optimization problems. However, the effectiveness of existing surrogate-assisted still needs improved. A data-driven sampling (DESO) framework is proposed, where at each generation it randomly employs one two strategies, surrogate screening and local search based ...

Extreme multi-label classification (XML) is becoming increasingly relevant in the era of big data. Yet, there no method for effectively generating stratified partitions XML datasets. Instead, researchers typically rely on provided test-train splits that, 1) aren’t always representative entire dataset, and 2) are missing many labels. This can lead to poor generalization ability unreliable perfor...