HyPockeTuner: Bringing Hyperparameter Optimization to Mobile Devices

要旨

Hyperparameter optimization (HPO) is a long-running process that can span hours or even days. While recent Human-in-the-Loop HPO systems enable monitoring and steering of the process, they are typically designed for desktop environments, which limits their effectiveness in managing prolonged experiments in practice. To address these limitations, we present HyPockeTuner, an interactive mobile system that enables users to monitor, steer, and reflect on HPO experiments anytime, anywhere from smartphones. Its mobile-tailored interface supports tracking experiment history and visualizing the relationship between user interventions and performance changes. HyPockeTuner also employs a notification workflow that alerts users to important events, reducing the burden of constant monitoring while enabling timely interventions. In a pilot study, we validated that users could readily identify critical events, such as performance improvements and intervention points, through our visualization. Furthermore, two five-day deployment studies with follow-up reflection sessions demonstrated that users could integrate experiment management into their daily routines and reflect on past decisions, generating insights for future improvement.

著者
Donghee Hong
Sungkyunkwan University, Suwon, Korea, Republic of
Bongshin Lee
Yonsei University, Seoul, Korea, Republic of
Jinwook Seo
Seoul National University, Seoul, Korea, Republic of
Jaemin Jo
Sungkyunkwan University, Suwon, Korea, Republic of

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI & Data Visualization

M2 - Room M211/212
6 件の発表
2026-04-15 18:00:00
2026-04-15 19:30:00