13 citations · 43 across the 9 of their papers we have counts for
4 papers · 1 filter
Privacy for Free in the Overparameterized Regime
Simone Bombari, Marco Mondelli
Differentially private gradient descent (DP-GD) is a popular algorithm to train deep learning models with provable guarantees on the privacy of the training data. In the last decad…
Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models
Yizhou Xu, TianQi Hou, ShanSuo Liang +1
We consider the problem of reconstructing the signal and the hidden variables from observations coming from a multi-layer network with rotationally invariant weight matrices. The m…
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models
Marco Mondelli, Ramji Venkataramanan
We study the problem of estimating a rank- signal in the presence of rotationally invariant noise-a class of perturbations more general than Gaussian noise. Principal Component…
Approximate Message Passing with Spectral Initialization for Generalized Linear Models
Marco Mondelli, Ramji Venkataramanan
We consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a famil…