Machine Learning with a twist: How trivial labels can be used to predict policy changes

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Julian TszKin Chan

Julian TszKin Chan is a senior economist at Bates White Economic Consulting. Weifeng Zhong is a research fellow in economic policy studies at the American Enterprise Institute.

Artificial Intelligence

Machine Learning with a twist: How trivial labels can be used to predict policy changes

November 1, 2018

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Julian TszKin Chan

Machine Learning with a twist: How trivial labels can be used to predict policy changes

LATEST ARTICLES

AlphaProteo uses AI in protein design

OpenAI’s this new model allegedly cost 2k USD

Google to let you Ask Photos directly—No more endless scrolling

HyperWrite’s Reflection 70B is here to fight against AI hallucinations

Disney data leak exposes financial and personal information amidst summer cybersecurity turmoil

“GPT Next” isn’t OpenAI’s next big thing, yet it will be still powerful

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