In practice, multiple conflicting objectives and costly evaluations (e.g., wet-lab experiments) make the diversity of candidates

To address issues of group-level fairness in machine learning, it is natural to adjust model parameters based on specific fairness objectives over a sensitive-attributed validation set.

Each sublayer adds a skip-connection (ADD) and batch normalization (BN). The decoder sequentially chooses a node according to a probability distribution produced by the node embeddings to construct a solution. The scaled symmetric sampling method is shown in Algorithm 2. The scaled factor The uniform division of the weight space is illustrated as follows. Thus, its approximate Pareto optimal solutions are commonly pursued. V ehicles must serve all the customers and finally return to the depot.

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