Variance-insensitive and Target-preserving Mask Refinement for Interactive Image Segmentation

no code implementations • 22 Dec 2023 • Chaowei Fang, Ziyin Zhou, Junye Chen, Hanjing Su, Qingyao Wu, Guanbin Li

We introduce a novel method, Variance-Insensitive and Target-Preserving Mask Refinement to enhance segmentation quality with fewer user inputs.

Image Segmentation Segmentation +1

Samplable Anonymous Aggregation for Private Federated Data Analysis

no code implementations • 27 Jul 2023 • Kunal Talwar, Shan Wang, Audra McMillan, Vojta Jina, Vitaly Feldman, Bailey Basile, Aine Cahill, Yi Sheng Chan, Mike Chatzidakis, Junye Chen, Oliver Chick, Mona Chitnis, Suman Ganta, Yusuf Goren, Filip Granqvist, Kristine Guo, Frederic Jacobs, Omid Javidbakht, Albert Liu, Richard Low, Dan Mascenik, Steve Myers, David Park, Wonhee Park, Gianni Parsa, Tommy Pauly, Christian Priebe, Rehan Rishi, Guy Rothblum, Michael Scaria, Linmao Song, Congzheng Song, Karl Tarbe, Sebastian Vogt, Luke Winstrom, Shundong Zhou

We revisit the problem of designing scalable protocols for private statistics and private federated learning when each device holds its private data.

Federated Learning

Differentially Private Heavy Hitter Detection using Federated Analytics

no code implementations • 21 Jul 2023 • Karan Chadha, Junye Chen, John Duchi, Vitaly Feldman, Hanieh Hashemi, Omid Javidbakht, Audra McMillan, Kunal Talwar

In this work, we study practical heuristics to improve the performance of prefix-tree based algorithms for differentially private heavy hitter detection.