5 papers
TSDS-Toolbox: A Toolbox for Measuring Time-Series Dataset Similarity
Yen-Ku Liu, Hongjie Chen, Ryan A. Rossi +1
The rapid advancement of artificial intelligence (AI) has significantly accelerated research in time-series analysis, particularly in forecasting, classification, and generation ta…
Quality-Driven Agentic Reasoning for LLM-Assisted Software Design: Questions-of-Thoughts (QoT) as a Time-Series Self-QA Chain
Yen-Ku Liu, Yun-Cheng Tsai
Recent advances in large language models (LLMs) have accelerated AI-assisted software development, yet practical deployment remains constrained by incomplete implementations, weak…
Q-A3C2: Quantum Reinforcement Learning with Time-Series Dynamic Clustering for Adaptive ETF Stock Selection
Yen-Ku Liu, Yun-Cheng Tsai, Samuel Yen-Chi Chen
Traditional ETF stock selection methods and reinforcement learning models such as the Asynchronous Advantage Actor-Critic (A3C) often suffer from high-dimensional feature spaces an…
Quantum-Enhanced Reinforcement Learning with LSTM Forecasting Signals for Optimizing Fintech Trading Decisions
Yen-Ku Liu, Yun-Huei Pan, Pei-Fan Lu +2
Financial trading environments are characterized by high volatility, numerous macroeconomic signals, and dynamically shifting market regimes, where traditional reinforcement learni…
Enhancing Interpretability of Quantum-Assisted Blockchain Clustering via AI Agent-Based Qualitative Analysis
Yun-Cheng Tsai, Yen-Ku Liu, Samuel Yen-Chi Chen
Blockchain transaction data is inherently high dimensional, noisy, and entangled, posing substantial challenges for traditional clustering algorithms. While quantum enhanced cluste…