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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…
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…
LLM-Based Routing in Mixture of Experts: A Novel Framework for Trading
Kuan-Ming Liu, Ming-Chih Lo
Recent advances in deep learning and large language models (LLMs) have facilitated the deployment of the mixture-of-experts (MoE) mechanism in the stock investment domain. While th…
Text2Freq: Learning Series Patterns from Text via Frequency Domain
Ming-Chih Lo, Ching Chang, Wen-Chih Peng
Traditional time series forecasting models mainly rely on historical numeric values to predict future outcomes.While these models have shown promising results, they often overlook…