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Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance
[article]
2020
arXiv
pre-print
Real-world applications often involve domain-specific and task-based performance objectives that are not captured by the standard machine learning losses, but are critical for decision making. A key challenge for direct integration of more meaningful domain and task-based evaluation criteria into an end-to-end gradient-based training process is the fact that often such performance objectives are not necessarily differentiable and may even require additional decision-making optimization
arXiv:1910.09357v4
fatcat:eltssi4gfzfh5juzj3nc74ssua