additive error
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- North America > United States > Maryland > Baltimore (0.14)
- North America > United States > California > San Francisco County > San Francisco (0.14)
- Asia > Afghanistan > Parwan Province > Charikar (0.04)
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- North America > United States > Maryland > Baltimore (0.14)
- North America > United States > California > San Francisco County > San Francisco (0.14)
- Asia > Afghanistan > Parwan Province > Charikar (0.04)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Clustering (0.68)
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- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- Oceania > New Zealand > North Island > Auckland Region > Auckland (0.04)
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Technology:
Differentially Private k-Means with Constant Multiplicative Error
Neural Information Processing Systems http://nips.cc/
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- North America > United States > California > San Francisco County > San Francisco (0.14)
- Oceania > Australia > New South Wales > Sydney (0.04)
- North America > United States > Texas > Harris County > Houston (0.04)
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The Price of Privacy for Low-rank Factorization
Unfortunately,existing private algorithm forLRFdo not consider thesesettings (except incentral model when matrices are received row by row [24]).
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- North America > United States > Maryland > Baltimore (0.04)
- North America > Canada > Quebec > Montreal (0.04)
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Submodular Function Minimization with Noisy Evaluation Oracle
Neural Information Processing Systems http://nips.cc/
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- North America > Canada (0.04)
- Asia > Middle East > Jordan (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
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Technology:
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- North America > United States > New York > New York County > New York City (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- Europe > Italy > Veneto > Venice (0.04)
- Europe > Finland > Uusimaa > Helsinki (0.04)
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k-Means Clustering with Distance-Based Privacy
In this paper, we initiate the study of Euclidean clustering with Distance-based privacy. Distance-based privacy is motivated by the fact that it is often only needed to protect the privacy of exact, rather than approximate, locations.
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- Europe > Czechia > Prague (0.04)
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
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