Search Results for author: Jonggyu Jang

Found 5 papers, 1 papers with code

Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network

no code implementations2 May 2024 Hyeonsu Lyu, Jonggyu Jang, Harim Lee, Hyun Jong Yang

We address a joint trajectory planning, user association, resource allocation, and power control problem to maximize proportional fairness in the aerial IoT network, considering practical end-to-end quality-of-service (QoS) and communication schedules.

Fairness Trajectory Planning

Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks

no code implementations4 Apr 2024 Minwoo Kim, Jonggyu Jang, Youngchol Choi, Hyun Jong Yang

In existing studies, joint optimization of overall task offloading and UA is seldom considered due to the complexity of combinatorial optimization problems, and in cases where it is considered, linear objective functions such as power consumption are adopted.

Combinatorial Optimization Edge-computing

Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach

no code implementations3 Apr 2024 Youjin Kim, Jonggyu Jang, Hyun Jong Yang

Despite the extensive research on massive MIMO systems for 5G telecommunications and beyond, the reality is that many deployed base stations are equipped with a limited number of antennas rather than supporting massive MIMO configurations.

Patch-MI: Enhancing Model Inversion Attacks via Patch-Based Reconstruction

no code implementations12 Dec 2023 Jonggyu Jang, Hyeonsu Lyu, Hyun Jong Yang

This approach allows the synthesis of images that are similar to the target dataset distribution, even in cases of dissimilar auxiliary dataset distribution.

Generative Adversarial Network

Deeper Understanding of Black-box Predictions via Generalized Influence Functions

1 code implementation9 Dec 2023 Hyeonsu Lyu, Jonggyu Jang, Sehyun Ryu, Hyun Jong Yang

However, growing non-convexity and the number of parameters in modern large-scale models lead to imprecise influence approximation and instability in computations.

Influence Approximation

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