4 papers
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…
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…