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Found 2 papers, 1 papers with code
High-dimensional Learning with Noisy Labels
This paper provides theoretical insights into high-dimensional binary classification with class-conditional noisy labels.
The Privacy Power of Correlated Noise in Decentralized Learning
Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data.
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