research
∙
02/02/2023
Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy
This work proposes Fed-GLOSS-DP, a novel approach to privacy-preserving ...
share
research
∙
10/11/2021
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
Federated learning is a powerful distributed learning scheme that allows...
research
∙
03/27/2021
Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling
This paper addresses the video rescaling task, which arises from the nee...
research
∙
11/28/2020
Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
While Generative Adversarial Networks (GANs) show increasing performance...
research
∙
05/20/2020
InfoScrub: Towards Attribute Privacy by Targeted Obfuscation
Personal photos of individuals when shared online, apart from exhibiting...
research
∙
09/10/2019
Learning Priors for Adversarial Autoencoders
Most deep latent factor models choose simple priors for simplicity, trac...
research
∙
03/26/2019