1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Extreme compression of sentence-transformer ranker models: faster inference, longer battery life, and less storage on edge devices
Amit Chaulwar, Lukas Malik, Maciej Krajewski +4
Modern search systems use several large ranker models with transformer architectures. These models require large computational resources and are not suitable for usage on devices w…
cs.CR2021
Secure Bayesian Federated Analytics for Privacy-Preserving Trend Detection
Amit Chaulwar, Michael Huth
Federated analytics has many applications in edge computing, its use can lead to better decision making for service provision, product development, and user experience. We propose…
cs.LG2020★ 1 cited
Private Dataset Generation Using Privacy Preserving Collaborative Learning
Amit Chaulwar
With increasing usage of deep learning algorithms in many application, new research questions related to privacy and adversarial attacks are emerging. However, the deep learning al…