weighted averaging algorithm
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- North America > United States > New York > New York County > New York City (0.05)
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Smoothly Bounding User Contributions in Differential Privacy
In many applications of differential privacy, a single user might contribute more than one data point. A prominent example, which is the focus of this paper, is private machine learning, where a user often provides several points in the training data set.
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- Europe > United Kingdom > Scotland > City of Edinburgh > Edinburgh (0.04)
- Oceania > Australia > Victoria > Melbourne (0.04)
- North America > United States > New Jersey > Mercer County > Princeton (0.04)
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Technology:
Smoothly Bounding User Contributions in Differential Privacy
In many applications of differential privacy, a single user might contribute more than one data point. A prominent example, which is the focus of this paper, is private machine learning, where a user often provides several points in the training data set.
Country:
- Europe > United Kingdom > Scotland > City of Edinburgh > Edinburgh (0.04)
- Oceania > Australia > Victoria > Melbourne (0.04)
- North America > United States > New Jersey > Mercer County > Princeton (0.04)
- (9 more...)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.48)