38 citations · 39 across the 9 of their papers we have counts for
11 papers
Coordinated Networking for On-Device Agent-Augmented Real-Time Communication
Goodsol Lee, Juheon Yi, Jinglu Wang +3
AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents autonomously retrieve, analyze,…
HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning
Jiseok Youn, You Rim Choi, Goodsol Lee +3
Mobile devices face diverse resource constraints and non-IID data class distributions, requiring fast on-device inference for local in-distribution (ID) classes and on-demand remot…
CORE: Robust Out-of-Distribution Detection via Confidence and Orthogonal Residual Scoring
Jin Mo Yang, Hyung-Sin Kim, Saewoong Bahk
Out-of-distribution (OOD) detection is essential for deploying deep learning models reliably, yet no single method performs consistently across architectures and datasets -- a scor…
Tracking the Discriminative Axis: Dual Prototypes for Test-Time OOD Detection Under Covariate Shift
Wooseok Lee, Jin Mo Yang, Saewoong Bahk +1
For reliable deployment of deep-learning systems, out-of-distribution (OOD) detection is indispensable. In the real world, where test-time inputs often arrive as streaming mixtures…
ALERT Open Dataset and Input-Size-Agnostic Vision Transformer for Driver Activity Recognition using IR-UWB
Jeongjun Park, Sunwook Hwang, Hyeonho Noh +3
Distracted driving contributes to fatal crashes worldwide. To address this, researchers are using driver activity recognition (DAR) with impulse radio ultra-wideband (IR-UWB) radar…
ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration
Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim +1
The growing use of 3D point cloud data in autonomous vehicles (AVs) has raised serious privacy concerns, particularly due to the sensitive information that can be extracted from 3D…
Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach
Jiseok Youn, Jaehun Song, Hyung-Sin Kim +1
Deep neural network quantization with adaptive bitwidths has gained increasing attention due to the ease of model deployment on various platforms with different resource budgets. I…
A Dual-Connection based Handover Scheme for Ultra-Dense Millimeter-Wave Cellular Networks
Seongjoon Kang, Siyoung Choi, Goodsol Lee +1
Mobile users in an ultra-dense millimeter-wave cellular network experience handover events more frequently than in conventional networks, which results in increased service interru…
Full-stack Hybrid Beamforming in mmWave 5G Networks
Felipe Gomez-Cuba, Tommaso Zugno, Junseok Kim +3
This paper analyzes Hybrid Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in millimeter wave (mmWave) 5th generation (5G) cellular networks considering t…
Hybrid Beamforming in 5G mmWave Networks: a Full-stack Perspective
Felipe Gomez-Cuba, Tommaso Zugno, Junseok Kim +3
This paper studies the cross-layer challenges and performance of Hybrid Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in 5G millimeter wave (mmWave) cel…
Large-scale Antenna Operation in Heterogeneous Cloud Radio Access Networks: A Partial Centralization Approach
Sangkyu Park, Chan-Byoung Chae, Saewoong Bahk
To satisfy the ever-increasing capacity demand and quality of service (QoS) requirements of users, 5G cellular systems will take the form of heterogeneous networks (HetNets) that c…