167 citations · 199 across the 8 of their papers we have counts for
8 papers
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance
Jingfeng Wu, Wennan Zhu, Peter Kairouz +1
In federated frequency estimation (FFE), multiple clients work together to estimate the frequencies of their collective data by communicating with a server that respects the privac…
Algorithms for bounding contribution for histogram estimation under user-level privacy
Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu +2
We study the problem of histogram estimation under user-level differential privacy, where the goal is to preserve the privacy of all entries of any single user. We consider the het…
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu +50
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…
Forming better stable solutions in Group Formation Games inspired by Internet Exchange Points (IXPs)
Elliot Anshelevich, Wennan Zhu
We study a coordination game motivated by the formation of Internet Exchange Points (IXPs), in which agents choose which facilities to join. Joining the same facility as other agen…
Awareness of Voter Passion Greatly Improves the Distortion of Metric Social Choice
Ben Abramowitz, Elliot Anshelevich, Wennan Zhu
We develop new voting mechanisms for the case when voters and candidates are located in an arbitrary unknown metric space, and the goal is to choose a candidate minimizing social c…
Federated Heavy Hitters Discovery with Differential Privacy
Wennan Zhu, Peter Kairouz, Brendan McMahan +2
The discovery of heavy hitters (most frequent items) in user-generated data streams drives improvements in the app and web ecosystems, but can incur substantial privacy risks if no…
Ordinal Approximation for Social Choice, Matching, and Facility Location Problems given Candidate Positions
Elliot Anshelevich, Wennan Zhu
In this work we consider general facility location and social choice problems, in which sets of agents and facilities are located in a metric space, and…
Tradeoffs Between Information and Ordinal Approximation for Bipartite Matching
Elliot Anshelevich, Wennan Zhu
We study ordinal approximation algorithms for maximum-weight bipartite matchings. Such algorithms only know the ordinal preferences of the agents/nodes in the graph for their prefe…