13 citations · 23 across the 11 of their papers we have counts for
5 papers · 1 filter
Parametric Feature Transfer: One-shot Federated Learning with Foundation Models
Mahdi Beitollahi, Alex Bie, Sobhan Hemati +4
In one-shot federated learning (FL), clients collaboratively train a global model in a single round of communication. Existing approaches for one-shot FL enhance communication effi…
DFML: Decentralized Federated Mutual Learning
Yasser H. Khalil, Amir H. Estiri, Mahdi Beitollahi +5
In the realm of real-world devices, centralized servers in Federated Learning (FL) present challenges including communication bottlenecks and susceptibility to a single point of fa…
Cross Domain Generative Augmentation: Domain Generalization with Latent Diffusion Models
Sobhan Hemati, Mahdi Beitollahi, Amir Hossein Estiri +3
Despite the huge effort in developing novel regularizers for Domain Generalization (DG), adding simple data augmentation to the vanilla ERM which is a practical implementation of t…
Understanding Hessian Alignment for Domain Generalization
Sobhan Hemati, Guojun Zhang, Amir Estiri +1
Out-of-distribution (OOD) generalization is a critical ability for deep learning models in many real-world scenarios including healthcare and autonomous vehicles. Recently, differe…
Mathematical Challenges in Deep Learning
Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev +8
Deep models are dominating the artificial intelligence (AI) industry since the ImageNet challenge in 2012. The size of deep models is increasing ever since, which brings new challe…