2 citations
6 papers
FedTVD: Balancing Data Quality and Quantity for Robust Federated Learning
Radwan Selo, Majid Kundroo, Taehong Kim
Federated Learning (FL) enables collaborative model training across distributed client devices while preserving data privacy. However, FL faces significant challenges due to data h…
FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning
Van Truong Vo, Khoa Nguyen, Taehong Kim
Decentralized intelligence systems with heterogeneous devices and limited coordination increasingly rely on decentralized federated learning (DFL). However, DFL suffers from conver…
FedLBW: A Loss-Based Weighting Strategy for Federated Learning on Non-IID Data in Wireless Networks
Majid Kundroo, Tinku Singh, Taehong Kim
Federated Learning (FL) enables collaborative machine learning (ML) across distributed clients while preserving privacy. However, efficient model convergence in FL remains challeng…
FedVAR: Prototype-Aligned Federated Framework for Video Anomaly Recognition
Ghani Haider, Majid Kundroo, Boyun Eom +3
In the era of Industrial Internet of Things (IIoT) and Cyber-Physical Systems (CPS), Federated Learning (FL) offers a promising decentralized intelligence paradigm for Video Anomal…
Existence of weak solutions for fast diffusion equation with a divergence type of drift term
Sukjung Hwang, Kyungkeun Kang, Hwa Kil Kim
We construct non-negative weak solutions of fast diffusion equations with a divergence type of drift term satisfying the -energy inequality and speed estimate in Wasserstein s…
Boson Stars Hosting Black Holes
Amitayus Banik, Jeong Han Kim, Xing-Yu Yang
We study a self-gravitating ultralight dark matter condensate (a boson star) hosting a central black hole, in the nonrelativistic limit, which we refer to as a boson star black hol…