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Found 4 papers, 0 papers with code
GLHF: General Learned Evolutionary Algorithm Via Hyper Functions
Pretrained Optimization Models (POMs) leverage knowledge gained from optimizing various tasks, providing efficient solutions for new optimization challenges through direct usage or fine-tuning.
Pre-trained transformer for adversarial purification
It is frightening that deep neural networks are vulnerable and sensitive to adversarial attacks, the most common one of which for the services is evasion-based.
B2Opt: Learning to Optimize Black-box Optimization with Little Budget
To achieve this, 1) drawing on the mechanism of genetic algorithm, we propose a deep neural network framework called B2Opt, which has a stronger representation of optimization strategies based on survival of the fittest; 2) B2Opt can utilize the cheap surrogate functions of the target task to guide the design of the efficient optimization strategies.
Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes
In this way, our proposal can better keep the advantages of previous community detection results and transfer them to the next task.
