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Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees
We address the problem of how to achieve optimal inference in distributed quantile regression without stringent scaling conditions.
An Unethical Optimization Principle
If an artificial intelligence aims to maximise risk-adjusted return, then under mild conditions it is disproportionately likely to pick an unethical strategy unless the objective function allows sufficiently for this risk.
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