collaborators

5 papers

cs.LG2025

Sensor Calibration Model Balancing Accuracy, Real-time, and Efficiency

Jinyong Yun, Hyungjin Kim, Seokho Ahn +2

Most on-device sensor calibration studies benchmark models only against three macroscopic requirements (i.e., accuracy, real-time, and resource efficiency), thereby hiding deployme…

cs.LG2025

Stochastic Deep Graph Clustering for Practical Group Formation

Junhyung Park, Hyungjin Kim, Seokho Ahn +1

While prior work on group recommender systems (GRSs) has primarily focused on improving recommendation accuracy, most approaches assume static or predefined groups, making them uns…

cs.CV2025

Draw Your Mind: Personalized Generation via Condition-Level Modeling in Text-to-Image Diffusion Models

Hyungjin Kim, Seokho Ahn, Young-Duk Seo

Personalized generation in T2I diffusion models aims to naturally incorporate individual user preferences into the generation process with minimal user intervention. However, exist…

cs.LG2025

SenDaL: An Effective and Efficient Calibration Framework of Low-Cost Sensors for Daily Life

Seokho Ahn, Hyungjin Kim, Euijong Lee +1

The collection of accurate and noise-free data is a crucial part of Internet of Things (IoT)-controlled environments. However, the data collected from various sensors in daily life…

cs.LG2024

Real-time Calibration Model for Low-cost Sensor in Fine-grained Time series

Seokho Ahn, Hyungjin Kim, Sungbok Shin +1

Precise measurements from sensors are crucial, but data is usually collected from low-cost, low-tech systems, which are often inaccurate. Thus, they require further calibrations. T…