17 citations · 30 across the 7 of their papers we have counts for
7 papers
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Kai Yi, Nidham Gazagnadou, Peter Richtárik +1
The interest in federated learning has surged in recent research due to its unique ability to train a global model using privacy-secured information held locally on each client. Th…
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma +3
Hand-crafted image quality metrics, such as PSNR and SSIM, are commonly used to evaluate model privacy risk under reconstruction attacks. Under these metrics, reconstructed images…
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space
Yuyang Deng, Nidham Gazagnadou, Junyuan Hong +2
Recent studies demonstrated that the adversarially robust learning under attack is harder to generalize to different domains than standard domain adaptation. How to t…
Cutting Some Slack for SGD with Adaptive Polyak Stepsizes
Robert M. Gower, Mathieu Blondel, Nidham Gazagnadou +1
Tuning the step size of stochastic gradient descent is tedious and error prone. This has motivated the development of methods that automatically adapt the step size using readily a…
: A Fast sketching based solver for large scale ridge regression
Nidham Gazagnadou, Mark Ibrahim, Robert M. Gower
We propose new variants of the sketch-and-project method for solving large scale ridge regression problems. Firstly, we propose a new momentum alternative and provide a theorem sho…
Towards closing the gap between the theory and practice of SVRG
Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi +2
Among the very first variance reduced stochastic methods for solving the empirical risk minimization problem was the SVRG method (Johnson & Zhang 2013). SVRG is an inner-outer loop…
Optimal mini-batch and step sizes for SAGA
Nidham Gazagnadou, Robert M. Gower, Joseph Salmon
Recently it has been shown that the step sizes of a family of variance reduced gradient methods called the JacSketch methods depend on the expected smoothness constant. In particul…