Anders Aamand

Postdoc@University of Copenhagen·丹麦·OpenReview

研究方向

Differential privacy · theory · graph structured data · Learning augmented algorithms · algorithms with predictions · learning theory · Hashing · sketching · streaming

发表论文（8 篇）

Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

合作者 (18)