activity
20182021
most citedROMark: A Robust Watermarking System Using Adversarial Training

30 citations · 37 across the 4 of their papers we have counts for

collaborators

8 papers

cs.LG2021

Differentially Private Query Release Through Adaptive Projection

Sergul Aydore, William Brown, Michael Kearns +4

We propose, implement, and evaluate a new algorithm for releasing answers to very large numbers of statistical queries like -way marginals, subject to differential privacy. Our…

cs.LG2021

Adversarial Robustness with Non-uniform Perturbations

Ecenaz Erdemir, Jeffrey Bickford, Luca Melis +1

Robustness of machine learning models is critical for security related applications, where real-world adversaries are uniquely focused on evading neural network based detectors. Pr…

cs.LG2020

Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression

Haleh Akrami, Anand A. Joshi, Sergul Aydore +1

Estimation of uncertainty in deep learning models is of vital importance, especially in medical imaging, where reliance on inference without taking into account uncertainty could l…

cs.LG20205 cited

Robust Variational Autoencoder for Tabular Data with Beta Divergence

Haleh Akrami, Sergul Aydore, Richard M. Leahy +1

We propose a robust variational autoencoder with divergence for tabular data (RTVAE) with mixed categorical and continuous features. Variational autoencoders (VAE) and their va…

cs.LG20192 cited

Dynamic Local Regret for Non-convex Online Forecasting

Sergul Aydore, Tianhao Zhu, Dean Foster

We consider online forecasting problems for non-convex machine learning models. Forecasting introduces several challenges such as (i) frequent updates are necessary to deal with co…

cs.CV201930 cited

ROMark: A Robust Watermarking System Using Adversarial Training

Bingyang Wen, Sergul Aydore

The availability and easy access to digital communication increase the risk of copyrighted material piracy. In order to detect illegal use or distribution of data, digital watermar…