吳沛遠副教授的著作列表 - Publication List of Pei-Yuan Wu

Publication List of 吳沛遠 Pei-Yuan Wu

Journal articles & book chapters:

  1. Hung Nguyen, Pei-Yuan Wu, J. Morris Chang, “Federated Learning for distribution skewed data using sample weights,” IEEE Transactions on Artificial Intelligence, Dec. 2023
  2. Wei-Jyun Hong, Chia-Yu Shen, Pei-Yuan Wu, “Multi-source wafer map retrieval based on contrastive learning for root cause analysis in semiconductor manufacturing,” Journal of Intelligent Manufacturing, Nov. 2023
  3. Po-Hsuan Huang, Chia-Heng Tu, Shen-Ming Chung, Pei-Yuan Wu, Tung-Lin Tsai, Yi-An Lin, Chun-Yi Dai, Tzu-Yi Liao, “SecureTVM: A TVM-Based Compiler Framework for Selective Privacy-Preserving Neural Inference,” ACM Transactions on Design Automation of Electronic Systems, 28, 1~28, May 2023
  4. Peng-Wen Chen, Tsung-Shan Yang, Gi-Luen Huang, Chia-Wen Huang, Yu-Chieh Chao, Chien-Hung Lu, Pei-Yuan Wu, “Viewing Bias Matters in 360° Videos Visual Saliency Prediction,” IEEE Access, Apr. 2023
  5. Tsung-Hsien Lin, Ying-Shuo Lee, Fu-Chieh Chang, J. Morris Chang, Pei-Yuan Wu, “Protecting Sensitive Attributes by Adversarial Training through Class-Overlapping Techniques,” IEEE Transactions on Information Forensics and Security, 18, 1283~1294, Jan. 2023
  6. Hao-Wei Chan, Pei-Yuan Wu, Alexander I-Chi Lai, Ruey-Beei Wu, “Fusion-Based Smartphone Positioning Using Unsupervised Calibration of Crowdsourced Wi-Fi FTM,” IEEE Access, 10, 96260~96272, Sept. 2022
  7. Chung-Yuan Chen, Alexander I-Chi Lai, Pei-Yuan Wu, Ruey-Beei Wu, “Optimization and Evaluation of Multi-Detector Deep Neural Network for High Accuracy Wi-Fi Fingerprint Positioning,” IEEE Internet of Things, 9(16), 15204~15214, Jan. 2022
  8. Poh Yuen Chan, Alexander I-Chi Lai, Pei-Yuan Wu, Ruey-Beei Wu, “Physical Tampering Detection Using Single COTS Wi-Fi Endpoint,” Sensors, 21(16), 5665, Aug. 2021
  9. Hung Nguyen, Di Zhuang, Pei-Yuan Wu, Morris Chang, “AutoGAN-based dimension reduction for privacy preservation,” Neurocomputing, vol. 384, 94~103, Apr. 2020
  10. B. Tseng and P. Wu , “Compressive Privacy Generative Adversarial Network,” IEEE Transactions on Information Forensics and Security, vol. 15, 2499~2513, Jan. 2020
  11. S. Y. Kung, Thee Chanyaswad, J. Morris Chang, and P. Y. Wu, “Collaborative PCA/DCA Learning Methods for Compressive Privacy,” ACM Transactions on Embedded Computing Systems, Volume 16 Issue 3, 76:1~76:18, Jul. 2017
  12. P. Y. Wu, C. C. Fang, J. M. Chang, and S. Y. Kung, “Cost-Effective Kernel Ridge Regression Implementation for Keystroke-Based Active Authentication System,” IEEE Trans. Cybern., vol. 47, no. 11, 3916~3927, Aug. 2016
  13. J. M. Chang, C. C. Fang, K. H. Ho, N. Kelly, P. Y. Wu, Y. Ding, C. Chu, S. Gilbert, A. E. Kamal, S. Y. Kung, “Capturing Cognitive Fingerprints from Keystroke Dynamics,” IT Professional, vol. 15, 24~28, Jul. 2013

Conference & proceeding papers:

  1. Po-Hung Yeh, Pei-Yuan Wu, Jun-Cheng Chen, “Improved Photometric Stereo through Efficient and Differentiable Shadow Estimation,” BMVC 2023, Aberdeen, Scotland, Nov. 2023
  2. Tung-Lin Tsai, Pei-Yuan Wu, “SepMM : A General Matrix Multiplication Optimization Approach for Privacy-Preserving Machine Learning,” IEEE Conference on Dependable and Secure Computing (IEEE DSC), Tampa, FL USA, Nov. 2023
  3. Hongxin Lin; Yunwei Chiu; Peiyuan Wu, “AMPose: Alternately Mixed Global-Local Attention Model for 3D Human Pose Estimation,” 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1~5, Rhodes Island, Greece, Jun. 2023
  4. SY Yeh, FC Chang, CW Yueh, PY Wu, A Bernacchia, S Vakili, “Sample Complexity of Kernel-Based Q-Learning,” International Conference on Artificial Intelligence and Statistics, 453~469, Valencia, Apr. 2023
  5. Fu-Chieh Chang, Farhang Nabiei, Pei-Yuan Wu, Alexandru Cioba, Sattar Vakili, Alberto Bernacchia, “Gradient Descent: Robustness to Adversarial Corruption,” NeurIPS Workshop: Optimization for Machine Learning, Dec. 2022
  6. Gi-Luen Huang and Pei-Yuan Wu, “CTGAN: Cloud Transformer Generative Adversarial Network,” IEEE International Conference on Image Processing, Bordeaux, France, Oct. 2022
  7. C. O. Ancuti et al., “NTIRE 2020 Challenge on NonHomogeneous Dehazing,” IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2029~2044, Seattle, WA, USA, Jun. 2020
  8. M. Al-Rubaie, P. Y. Wu, J. M. Chang and S. Y. Kung, “Privacy-preserving PCA on horizontally-partitioned data,” 2017 IEEE Conference on Dependable and Secure Computing, 280~287, Taipei, Taiwan, Aug. 2017
  9. S. Y. Kung and P. Y. Wu, “A Partial Cosine Kernel Approach to Incomplete Data Analysis,” Int’l Conf. on Advances in Big Data Analysis (ABDA), 95~101, Las Vegas, Jul. 2014
  10. P. Y. Wu, C. C. Fang, J. M. Chang, S. Gilbert, and S. Y. Kung, “Cost-Effective Kernel Ridge Regression for Keystroke-Based Active Authentication System,” ICASSP, 6028~6032, Florence, May 2014
  11. C. H. Lu and P. Y. Wu, “Using Density Invariant Graph Laplacian to Resolve Unobservable Parameters for Three-Dimensional Optical Bio-Imaging,” Int’l Conf. Acoustic, Speech, Signal Proc. (ICASSP), 1621~1625, Florence, May 2014
  12. S. Y. Kung and P. Y. Wu, “Perturbation Regulated Kernel Regressors for Supervised Machine Learning,” Int’l Workshop on Machine Learning for Signal Processing (MLSP), 1~6, Santander, Sept. 2012
  13. S. Y. Kung and P. Y. Wu, “On Efficient Learning and Classification Kernel Methods,” ICASSP, 2065~2068, Kyoto, Mar. 2012

Patents:

  1. Chia-Feng Liao, Chun-Hsien Lin, Pei-Yi Su, Yi-Ming Dai, Chung-Hsing Lee, Chien-Ko Liao, Chun-Yung Chang, Nan-Jung Chen, Pei-Yuan Wu, Hsien-Mao Huang, “Photolithography tool and method thereof,” US20170123328A1 , Jan. 2017