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On ranking via sorting by estimated expected utility
We provide an answer to this question in the form of a structural characterization of ranking losses for which a suitable regression is consistent.
Embedding models for recommendation under contextual constraints
For example, applying constraints a posteriori can result in incomplete recommendations or low-quality results for the tail of the distribution (i. e., less popular items).
Improving Evolutionary Strategies with Generative Neural Networks
Evolutionary Strategies (ES) are a popular family of black-box zeroth-order optimization algorithms which rely on search distributions to efficiently optimize a large variety of objective functions.
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