Search Results for author:
Found 3 papers, 1 papers with code
FastLloyd: Federated, Accurate, Secure, and Tunable $k$-Means Clustering with Differential Privacy
By utilizing the computational DP model, we design a lightweight, secure aggregation-based approach that achieves four orders of magnitude speed-up over state-of-the-art related work.
Leveraging Optimization for Adaptive Attacks on Image Watermarks
A core security property of watermarking is robustness, which states that an attacker can only evade detection by substantially degrading image quality.
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions
Motivated by the success of previous work co-designing machine learning and MPC, we develop an activation function co-design.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
