10 citations · 18 across the 4 of their papers we have counts for
6 papers
Fairness in Federated Learning: Trends, Challenges, and Opportunities
Noorain Mukhtiar, Adnan Mahmood, Quan Z. Sheng
At the intersection of the cutting-edge technologies and privacy concerns, Federated Learning (FL) with its distributed architecture, stands at the forefront in a bid to facilitate…
Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning
Xiyu Zhao, Qimei Cui, Weicai Li +5
Personalized federated learning (PFL), e.g., the renowned Ditto, strikes a balance between personalization and generalization by conducting federated learning (FL) to guide persona…
A Novel Indicator for Quantifying and Minimizing Information Utility Loss of Robot Teams
Xiyu Zhao, Qimei Cui, Wei Ni +5
The timely exchange of information among robots within a team is vital, but it can be constrained by limited wireless capacity. The inability to deliver information promptly can re…
SDVPT: Semantic-Driven Visual Prompt Tuning for Open-World Object Counting
Yiming Zhao, Guorong Li, Laiyun Qing +5
Open-world object counting leverages the robust text-image alignment of pre-trained vision-language models (VLMs) to enable counting of arbitrary categories in images specified by…
LGL-BCI: A Motor-Imagery-Based Brain-Computer Interface with Geometric Learning
Jianchao Lu, Yuzhe Tian, Yang Zhang +2
Brain--computer interfaces are groundbreaking technology whereby brain signals are used to control external devices. Despite some advances in recent years, electroencephalogram (EE…
BGTplanner: Maximizing Training Accuracy for Differentially Private Federated Recommenders via Strategic Privacy Budget Allocation
Xianzhi Zhang, Yipeng Zhou, Miao Hu +4
To mitigate the rising concern about privacy leakage, the federated recommender (FR) paradigm emerges, in which decentralized clients co-train the recommendation model without expo…