99 citations · 222 across the 29 of their papers we have counts for
31 papers
Batch Clipping and Adaptive Layerwise Clipping for Differential Private Stochastic Gradient Descent
Toan N. Nguyen, Phuong Ha Nguyen, Lam M. Nguyen +1
Each round in Differential Private Stochastic Gradient Descent (DPSGD) transmits a sum of clipped gradients obfuscated with Gaussian noise to a central server which uses this to up…
Considerations on the Theory of Training Models with Differential Privacy
Marten van Dijk, Phuong Ha Nguyen
In federated learning collaborative learning takes place by a set of clients who each want to remain in control of how their local training data is used, in particular, how can eac…
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis
Quoc Tran-Dinh, Marten van Dijk
In this book chapter, we briefly describe the main components that constitute the gradient descent method and its accelerated and stochastic variants. We aim at explaining these co…
Generalizing DP-SGD with Shuffling and Batch Clipping
Marten van Dijk, Phuong Ha Nguyen, Toan N. Nguyen +1
Classical differential private DP-SGD implements individual clipping with random subsampling, which forces a mini-batch SGD approach. We provide a general differential private algo…
Finite-Sum Optimization: A New Perspective for Convergence to a Global Solution
Lam M. Nguyen, Trang H. Tran, Marten van Dijk
Deep neural networks (DNNs) have shown great success in many machine learning tasks. Their training is challenging since the loss surface of the network architecture is generally n…
Secure Remote Attestation with Strong Key Insulation Guarantees
Deniz Gurevin, Chenglu Jin, Phuong Ha Nguyen +2
Recent years have witnessed a trend of secure processor design in both academia and industry. Secure processors with hardware-enforced isolation can be a solid foundation of cloud…