activity
20072024
most citedFederated Learning over Wireless Networks: Convergence Analysis and Resource Allocation

409 citations · 2.9k across the 98 of their papers we have counts for

collaborators

104 papers

q-fin.ST2024★ 5 cited

Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting

Chu Myaet Thwal, Ye Lin Tun, Kitae Kim +2

Recent innovations in transformers have shown their superior performance in natural language processing (NLP) and computer vision (CV). The ability to capture long-range dependenci…

cs.LG2024★ 24 cited

Attention on Personalized Clinical Decision Support System: Federated Learning Approach

Chu Myaet Thwal, Kyi Thar, Ye Lin Tun +1

Health management has become a primary problem as new kinds of diseases and complex symptoms are introduced to a rapidly growing modern society. Building a better and smarter healt…

cs.IT2023★ 2 cited

Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks

Christo Kurisummoottil Thomas, Christina Chaccour, Walid Saad +2

Despite the basic premise that next-generation wireless networks (e.g., 6G) will be artificial intelligence (AI)-native, to date, most existing efforts remain either qualitative or…

cs.NI2023

Deep Reinforcement Learning based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications

Pyae Sone Aung, Loc X. Nguyen, Yan Kyaw Tun +2

Vehicle-to-Everything (V2X) communications play a crucial role in ensuring safe and efficient modern transportation systems. However, challenges arise in scenarios with buildings,…

cs.NI2023★ 1 cited

SpaceRIS: LEO Satellite Coverage Maximization in 6G Sub-THz Networks by MAPPO DRL and Whale Optimization

Sheikh Salman Hassan, Yu Min Park, Yan Kyaw Tun +3

Satellite systems face a significant challenge in effectively utilizing limited communication resources to meet the demands of ground network traffic, characterized by asymmetrical…

cs.IT2023

Convergence of Communications, Control, and Machine Learning for Secure and Autonomous Vehicle Navigation

Tengchan Zeng, Aidin Ferdowsi, Omid Semiari +2

Connected and autonomous vehicles (CAVs) can reduce human errors in traffic accidents, increase road efficiency, and execute various tasks ranging from delivery to smart city surve…