3 papers
cs.LG2025
Perseus: Interactive Time Series Segmentation with Sparse Supervision via Stateful Memory
Ching Chang, Ming-Chih Lo, Chiao-Tung Chan +2
Real-world systems, ranging from industrial manufacturing to wearable healthcare, generate multivariate time series with hierarchical states ranging from coarse regimes to fine-gra…
cs.LG2025
PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation
Ching Chang, Ming-Chih Lo, Wen-Chih Peng +1
Multivariate time series data, collected across various fields such as manufacturing and wearable technology, exhibit states at multiple levels of granularity, from coarse-grained…
cs.LG2025
LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters
Ching Chang, Wei-Yao Wang, Wen-Chih Peng +1
Multivariate time-series forecasting is vital in various domains, e.g., economic planning and weather prediction. Deep train-from-scratch models have exhibited effective performanc…