17 citations · 28 across the 8 of their papers we have counts for
6 papers · 1 filter
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges
Vishnu Pandi Chellapandi, Liangqi Yuan, Christopher G. Brinton +2
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles (CAV), including perception, planning, and control. However, its reliance on vehicular data f…
Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
Yongjeong Oh, Jaeho Lee, Christopher G. Brinton +1
This paper proposes a novel communication-efficient split learning (SL) framework, named SplitFC, which reduces the communication overhead required for transmitting intermediate fe…
Exploring the Efficacy of ChatGPT in Analyzing Student Teamwork Feedback with an Existing Taxonomy
Andrew Katz, Siqing Wei, Gaurav Nanda +2
Teamwork is a critical component of many academic and professional settings. In those contexts, feedback between team members is an important element to facilitate successful and s…
Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning
Junghoon Kim, Taejoon Kim, David Love +1
The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated s…
Delay-Aware Hierarchical Federated Learning
Frank Po-Chen Lin, Seyyedali Hosseinalipour, Nicolò Michelusi +1
Federated learning has gained popularity as a means of training models distributed across the wireless edge. The paper introduces delay-aware hierarchical federated learning (DFL)…
Digital Over-the-Air Federated Learning in Multi-Antenna Systems
Sihua Wang, Mingzhe Chen, Cong Shen +2
In this paper, the performance optimization of federated learning (FL), when deployed over a realistic wireless multiple-input multiple-output (MIMO) communication system with digi…