Search Results for author:
Found 2 papers, 0 papers with code
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
As an application of our analysis, we show that PTR and our theoretical results can be used to design differentially private variants for byzantine robust training algorithms that use robust statistics for gradients aggregation.
Choosing the Right Algorithm With Hints From Complexity Theory
Our finding that the unary unbiased black-box complexity is only $O(n^2)$ suggests the Metropolis algorithm as an interesting candidate and we prove that it solves the DLB problem in quadratic time.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
