1 citations · 1 across the 4 of their papers we have counts for
4 papers
Revisiting GAN with Bayes-Optimal Discrimination
Mohammadreza Tavasoli Naeini, Ali Bereyhi, Morteza Noshad +2
We approach generative adversarial network (GAN) training from its original real-versus-fake classification viewpoint, replacing the cross-entropy discriminator objective with an u…
Coupled Data and Measurement Space Dynamics for Enhanced Diffusion Posterior Sampling
Shayan Mohajer Hamidi, En-Hui Yang, Ben Liang
Inverse problems, where the goal is to recover an unknown signal from noisy or incomplete measurements, are central to applications in medical imaging, remote sensing, and computat…
BOLT: Universal Classifier Training via a Bayes-Error Upper Bound
Mohammadreza Tavasoli Naeini, Ali Bereyhi, Morteza Noshad +2
This work introduces a novel approach to compute a universal upper bound on the Bayes error rate (BER) from classifier-output samples, which serves as a Bayes-error-related perform…
Regularized Top-: A Bayesian Framework for Gradient Sparsification
Ali Bereyhi, Ben Liang, Gary Boudreau +1
Error accumulation is effective for gradient sparsification in distributed settings: initially-unselected gradient entries are eventually selected as their accumulated error exceed…