14 citations · 39 across the 11 of their papers we have counts for
11 papers · 1 filter
Personalized Online Federated Learning with Multiple Kernels
Pouya M. Ghari, Yanning Shen
Multi-kernel learning (MKL) exhibits well-documented performance in online non-linear function approximation. Federated learning enables a group of learners (called clients) to tra…
Model Extraction Attacks Against Reinforcement Learning Based Controllers
Momina Sajid, Yanning Shen, Yasser Shoukry
We introduce the problem of model-extraction attacks in cyber-physical systems in which an attacker attempts to estimate (or extract) the feedback controller of the system. Extract…
FairGAT: Fairness-aware Graph Attention Networks
O. Deniz Kose, Yanning Shen
Graphs can facilitate modeling various complex systems such as gene networks and power grids, as well as analyzing the underlying relations within them. Learning over graphs has re…
FairNorm: Fair and Fast Graph Neural Network Training
O. Deniz Kose, Yanning Shen
Graph neural networks (GNNs) have been demonstrated to achieve state-of-the-art for a number of graph-based learning tasks, which leads to a rise in their employment in various dom…
Graph-Assisted Communication-Efficient Ensemble Federated Learning
Pouya M Ghari, Yanning Shen
Communication efficiency arises as a necessity in federated learning due to limited communication bandwidth. To this end, the present paper develops an algorithmic framework where…
Fair Node Representation Learning via Adaptive Data Augmentation
O. Deniz Kose, Yanning Shen
Node representation learning has demonstrated its efficacy for various applications on graphs, which leads to increasing attention towards the area. However, fairness is a largely…