Author

Jonghun Park

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#artificial intelligence Preprint Sep 2026

Pseudo-Label-Triggered Retraining from Forecast Errors for Online Time Series Forecasting

Real-world time series forecasting systems operate under non-stationary data streams, where forecasting performance may degrade over time. Although retraining can recover the performance, it incurs non-trivial computational and operational costs. Under limited deployment resources, the key challenge is therefore not on...

Yeryeong Kwak, Yoo-Min Jung, Jonghun Park · 0 citations

#artificial intelligence Preprint Sep 2026

MASCIT: A Mask-Aware State Space Classifier for Naturally Irregular Time Series

The proposed mask-aware state space classifier for irregular time series (MASCIT), which supplies observation masks to the encoder and excludes invalid steps from gated temporal aggregation, supports selective state space models as effective, executable backbones for naturally irregular time series classification.

Yoo-Min Jung, Hyeon-Gi Kim, Jonghun Park · 0 citations