6 papers
Faithful and Fast Influence Function via Advanced Sampling
Jungyeon Koh, Hyeonsu Lyu, Jonggyu Jang +1
How can we explain the influence of training data on black-box models? Influence functions (IFs) offer a post-hoc solution by utilizing gradients and Hessians. However, computing t…
Joint Optimization of User Association and Resource Allocation for Load Balancing With Multi-Level Fairness
Jonggyu Jang, Hyeonsu Lyu, David J. Love +1
User association, the problem of assigning each user device to a suitable base station, is increasingly crucial as wireless networks become denser and serve more users with diverse…
Fed-ZOE: Communication-Efficient Over-the-Air Federated Learning via Zeroth-Order Estimation
Jonggyu Jang, Hyeonsu Lyu, David J. Love +1
As 6G and beyond networks grow increasingly complex and interconnected, federated learning (FL) emerges as an indispensable paradigm for securely and efficiently leveraging decentr…
Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network
Hyeonsu Lyu, Jonggyu Jang, Harim Lee +1
We address a joint trajectory planning, user association, resource allocation, and power control problem to maximize proportional fairness in the aerial IoT network, considering pr…
Rethinking Model Inversion Attacks With Patch-Wise Reconstruction
Jonggyu Jang, Hyeonsu Lyu, Hyun Jong Yang
Model inversion (MI) attacks aim to infer or reconstruct the training dataset through reverse-engineering from the target model's weights. Recently, significant advancements in gen…
Replace-then-Perturb: Targeted Adversarial Attacks With Visual Reasoning for Vision-Language Models
Jonggyu Jang, Hyeonsu Lyu, Jungyeon Koh +1
The conventional targeted adversarial attacks add a small perturbation to an image to make neural network models estimate the image as a predefined target class, even if it is not…