Publications

Conference Papers:

• Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, Zhiqiang Xu, Jing Jiang, Xiang Yin. “Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective”. NeurIPs 2023.
• Zhi Li, Pengfei Wei, Xiang Yin, Zejun Ma, Alex Kot. “Virtual Try-On with Pose-Garment Keypoints Guided Inpainting”. ICCV 2023.
• Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma. “S2CD-VC: Self-heuristic Speaker Content Disentanglement for Any-to-Any Voice Conversion”. Interspeech 2023.
• Xinghua Qu, Xiang Yin, Pengfei Wei, Lu Lu, Zejun Ma. “AudioQR: Deep Neural Audio Watermarks For QR Code”. International Joint Conference on Artificial Intelligence (IJCAI), 2023.
• Han Zheng, Xufang Luo, Pengfei Wei, Xuan Song, Dongsheng Li, Jin Jiang. “Adaptive Policy Learning for Offline-to-Online Reinforcement Learning”. 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
• Pengfei Wei, Xinghua Qu, Wen Song, Zejun Ma. “Dynamic Transfer Gaussian Process Regression”. 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
• Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang, Tze Yun Leong. “Adaptive Multi-Source Causal Inference from Observational Data”. 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
• Xinghua Qu, Pengfei Wei, Mingyong Gao, Zhu Sun, Yew-Soon Ong, Zejun Ma. “Synthesising Audio Adversarial Examples for Automatic Speech Recognition”. ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022.
• Xinghua Qu, Yew-Soon Ong, Abhishek Gupta, Pengfei Wei, Zhu Sun, Zejun Ma. “Importance Prioritized Policy Distillation”, ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022.
• Yizhou Lu, Mingkun Huang, Xinghua Qu, Pengfei Wei, Zejun Ma. “Language adaptive cross-lingual speech representation learning with sparse sharing sub-networks”. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022. (PDF)
• Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze Yun Leong. “Causal Modeling with Stochastic Confounders”. The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021, Online. (PDF)
• Pengfei Wei, Yiping Ke, Zhiqiang Xu, and Tze Yun Leong. “Succinct Adaptive Manifold Transfer”. International Confe rence on Information and Knowledge Management (CIKM), 2020, Ireland, Online. (PDF)
• Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, and Yi Chang. “MESA: Effective Ensemble Imbalanced Learning with MEta SAmpler”. Neural Information Processing Systems (NeurIPS), 2020, Online. (PDF)
• Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, and Chengqi Zhang. “Cooperative Heterogeneous Deep Reinforcement Learning”. Neural Information Processing Systems (NeurIPS), 2020, Online. (PDF)
• Pengfei Wei, Tze Yun Leong. “Randomized Transferable Machine”. International Conference on Pattern Recognition (ICPR), 2020, Online. (PDF)
• Pengfei Wei, Xinhua Qu, Yiping Ke, Tze Yun Leong, and Yew Soon Ong. “Adaptive Knowledge Transfer based on Transfer Neural Kernel Network”. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020, 1485-1493. (PDF)
• Han Zheng, Jing Jiang, Pengfei Wei, Guodong Long, Chengqi Zhang. “Competitive and Cooperative Heterogeneous Deep Reinforcement Learning”. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020, 1656-1664. (PDF)
• Pengfei Wei, Yiping Ke. “Knowledge Transfer based on Multiple Manifolds Assumption”. International Conference on Information and Knowledge Management (CIKM), 2019, Beijing, China, 279-287. (PDF)
• Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, Zhifeng Hao. “Learning Disentangled Semantic Representation for Domain Adaptation”, International Joint Conference on Artificial Intelligence (IJCAI), 2019, 2060–2066. (PDF)
• Pengfei Wei, Ramon Sagarna, Yiping Ke, Yew Soon Ong. “Uncluttered Domain Sub-similarity for Transfer Regression”, International Conference on Data Mining (ICDM), 2018, 1314-1319. (PDF)
• Tianbo Li, Pengfei Wei, and Yiping Ke. “Transfer Hawkes Processes with Content Information”, International Conference on Data Mining (ICDM), 2018, 1116-1121. (PDF)
• Pengfei Wei, Ramon Sagarna, Yiping Ke, Yew Soon Ong, Chi Keong Goh. “Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression”, International Conference on Machine Learning (ICML), 2017, 3722-3731. (PDF)
• Pengfei Wei, Yiping Ke, Chi Keong Goh. “Domain Specific Feature Transfer for Hybrid Domain Adaptation”, International Conference on Data Mining (ICDM), 2017, 1027-1032. (PDF)
• Pengfei Wei, Yiping Ke, Chi Keong Goh. “Deep Nonlinear Feature Coding for Unsupervised Domain Adaptation”, International Joint Conference on Artificial Intelligence (IJCAI), 2016, 2189-2195. (PDF)

Journal Papers:

• Pengfei Wei, Yiping Ke, Yew Soon Ong, Zejun Ma. “Adaptive Transfer Kernel Learning for Transfer Gaussian Process Regression”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.
• Pengfei Wei, Thanh Vinh Vo, Xinghua Qu, Yew Soon Ong, Zejun Ma. “Transfer Kernel Learning for Multi-source Transfer Gaussian Process Regression”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022. (PDF)
• Zhonghao Zhang, Qiqiang Li, Wen Song, Pengfei Wei, and Jing Guo. “A novel concavity based method for automatic segmentation of touching cells in microfluidic chips.” Expert Systems with Applications, 2022. (PDF)
• Pengfei Wei, Yiping Ke, Xinghua Qu, Tze Yun Leong. “Subdomain Adaptation with Manifolds Discrepancy Alignment”, IEEE Transactions on Cybernetics, 2021. (PDF)
• Pengfei Wei, Ramon Sargana, Yiping Ke, Yew Soon Ong. “Easy-but-effective Domain Sub-similarity Learning for Transfer Regression”, IEEE Transactions on Knowledge and Data Engineering, 2020. (PDF)
• Pengfei Wei, Ramon Sargana, Yiping, Ke, Yew Soon Ong. “Practical Multisource Transfer Regression with Source–Target Similarity Captures”, IEEE Transactions on Neural Networks and Learning systems, 2020. (PDF)
• Zhiqiang Xu, Yiping Ke, Xin Cao, Chunlai Zhou, Pengfei Wei, Xin Gao. “A unified linear convergence analysis of k-SVD”, Memetic Computing, 2020. (PDF)
• Xinghua Qu, Zhu Sun, Yew Soon Ong, Abhishek Gupta and Pengfei Wei. “Minimalistic Attacks: How Little it Takes to Fool Deep Reinforcement Learning Policies”. IEEE Transactions on Cognitive and Developmental Systems, 2020. (PDF)
• Xiurui Xie, Guisong Liu, Qing Cai, Pengfei Wei, and Hong Qu. “Multi-source sequential knowledge regression by using transfer RNN units”, Neural Networks 119 (2019): 151-161. (PDF)
• Pengfei Wei, Yiping Ke, Chi Keong Goh. “Feature Analysis of Marginalized Stacked Denoising Autoenconder for Unsupervised Domain Adaptation”, IEEE transactions on neural networks and learning systems 30.5 (2018): 1321-1334. (PDF)
• Pengfei Wei, Yiping Ke, Chi Keong Goh. “A General Domain Specific Feature Transfer Framework for Hybrid Domain Adaptation”, IEEE Transactions on Knowledge and Data Engineering 31.8 (2018): 1440-1451. (PDF)
• Lijiang Chen, Xia Mao, Pengfei Wei, Yuli Xue, Mitsuru Ishizuka. “Mandarin Emotion Recognition Combining Acoustic and Emotional Point Information”, Applied Intelligence 37.4 (2012): 602-612. (PDF)
• Lijiang Chen, Xia Mao, Pengfei Wei, Angelo Compare. “Speech Emotional Features Extraction Based on Electroglottograph”, Neural computation 25.12 (2013): 3294-3317. (PDF)