Author

Ming Jin

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#machine learning Preprint Aug 2026

Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs

A novel framework of temporal memory-aware Online Test-Time Adaptation on Dynamic Graphs, named DGOTTA, to effectively adapt well-trained DGNNs during test time and significantly improves generalization under diverse distribution shifts and multiple model architectures is proposed.

Bo Li, Xin Zheng, Ming Jin et al. · 0 citations

#machine learning May 2025

Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting

The Continuous Evolution Pool (CEP), a replay-free framework that maintains a dynamic pool of specialized forecasters, is proposed, which employs a retrieval mechanism to identify the nearest concept based on gene similarity, an evolution strategy to spawn new forecasters upon detecting distribution shifts, and an elimination policy to prune obsolete models under memory constraints.

Tianxiang Zhan, Ming Jin, Yuanpeng He et al. · arXiv.org · 3 citations