Representation Learning on Large and Small Data. - Chun-Nan Chou; Chuen-Kai Shie; Fu-Chieh Chang 001; Jocelyn Chang; Edward Y. Chang (CoRR, 2017)

Toward Fusing Domain Knowledge with Generative Adversarial Networks to Improve Supervised Learning for Medical Diagnoses. - Fu-Chieh Chang 001; Jocelyn Chang; Chun-Nan Chou; Edward Y. Chang (MIPR, 2019)

G2R Bound: A Generalization Bound for Supervised Learning from GAN-Synthetic Data. - Fu-Chieh Chang 001; Hao-Jen Wang; Chun-Nan Chou; Edward Y. Chang (CoRR, 2019)

Flexible chip placement via reinforcement learning: late breaking results. - Fu-Chieh Chang 001; Yu-Wei Tseng; Ya-Wen Yu; Ssu-Rui Lee; Alexandru Cioba; I-Lun Tseng; Da-Shan Shiu; Jhih-Wei Hsu; Cheng-Yuan Wang; Chien-Yi Yang; Ren-Chu Wang; Yao-Wen Chang; et al. (DAC, 2022)

Flexible Multiple-Objective Reinforcement Learning for Chip Placement. - Fu-Chieh Chang 001; Yu-Wei Tseng; Ya-Wen Yu; Ssu-Rui Lee; Alexandru Cioba; I-Lun Tseng; Da-Shan Shiu; Jhih-Wei Hsu; Cheng-Yuan Wang; Chien-Yi Yang; Ren-Chu Wang; Yao-Wen Chang; et al. (CoRR, 2022)

Sample Complexity of Kernel-Based Q-Learning. - Sing-Yuan Yeh; Fu-Chieh Chang 001; Chang-Wei Yueh; Pei-Yuan Wu; Alberto Bernacchia; Sattar Vakili (AISTATS, 2023)

Protecting Sensitive Attributes by Adversarial Training Through Class-Overlapping Techniques. - Tsung-Hsien Lin; Ying-Shuo Lee; Fu-Chieh Chang 001; J. Morris Chang; Pei-Yuan Wu (IEEE Trans. Inf. Forensics Secur., 2023)

CAPM: Fast and Robust Verification on Maxpool-based CNN via Dual Network. - Jia-Hau Bai; Chi-Ting Liu; Yu Wang; Fu-Chieh Chang 001; Pei-Yuan Wu (CoRR, 2024)

RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner. - Fu-Chieh Chang 001; Yu-Ting Lee; Hui-Ying Shih; Pei-Yuan Wu (CoRR, 2024)

Unraveling Arithmetic in Large Language Models: The Role of Algebraic Structures. - Fu-Chieh Chang 001; Pei-Yuan Wu (CoRR, 2024)

RAD-Bench: Evaluating Large Language Models' Capabilities in Retrieval Augmented Dialogues. - Tzu-Lin Kuo; Fengting Liao; Mu-Wei Hsieh; Fu-Chieh Chang 001; Po-Chun Hsu; Da-shan Shiu (NAACL (Industry Track), 2025)

Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning. - Yen-Ru Lai; Fu-Chieh Chang 001; Pei-Yuan Wu (Trans. Mach. Learn. Res., 2025)

Chain-of-Thought Prompting for Out-of-Distribution Samples: A Latent-Variable Study. - Yu Wang; Fu-Chieh Chang 001; Pei-Yuan Wu (CoRR, 2025)

An Explanation of Intrinsic Self-Correction via Linear Representations and Latent Concepts. - Yu-Ting Lee; Hui-Ying Shih; Fu-Chieh Chang 001; Pei-Yuan Wu (CoRR, 2025)