Search Results for author: Milad Jalali Asadabadi

Found 2 papers, 0 papers with code

Differentially Private Data Generation Needs Better Features

no code implementations25 May 2022 Fredrik Harder, Milad Jalali Asadabadi, Danica J. Sutherland, Mijung Park

Training even moderately-sized generative models with differentially-private stochastic gradient descent (DP-SGD) is difficult: the required level of noise for reasonable levels of privacy is simply too large.

Transfer Learning

One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model

no code implementations2 May 2022 Wonho Bae, Junhyug Noh, Milad Jalali Asadabadi, Danica J. Sutherland

Semi-weakly supervised semantic segmentation (SWSSS) aims to train a model to identify objects in images based on a small number of images with pixel-level labels, and many more images with only image-level labels.

pseudo label Weakly-Supervised Semantic Segmentation

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