研究成果

第 1 到 23 筆結果，共 23 筆。

公開日期標題作者來源出版物scopusWOS全文
12023Federated Learning for distribution skewed data using sample weightsNguyen, Hung; PEI-YUAN WU ; Chang, J. MorrisIEEE Transactions on Artificial Intelligence
22023Viewing Bias Matters in 360° Videos Visual Saliency PredictionChen, Peng Wen; Yang, Tsung Shan; Huang, Gi Luen; Huang, Chia Wen; Chao, Yu Chieh; Lu, Chien Hung; PEI-YUAN WU IEEE Access00
32023Multi-source wafer map retrieval based on contrastive learning for root cause analysis in semiconductor manufacturingHong, Wei Jyun; Shen, Chia Yu; PEI-YUAN WU Journal of Intelligent Manufacturing0
42023Sample Complexity of Kernel-Based Q-LearningYeh, Sing Yuan; Chang, Fu Chieh; Yueh, Chang Wei; PEI-YUAN WU ; Bernacchia, Alberto; Vakili, SattarProceedings of Machine Learning Research0
52022CTGAN: CLOUD TRANSFORMER GENERATIVE ADVERSARIAL NETWORKHuang, Gi Luen; PEI-YUAN WU Proceedings - International Conference on Image Processing, ICIP20
62021Physical tampering detection using single cots wi?fi endpointChan P.Y; Lai A.I.-C; PEI-YUAN WU ; RUEY-BEEI WU Sensors76
72020AutoGAN-based dimension reduction for privacy preservationNguyen H; Zhuang D; PEI-YUAN WU ; Chang M.Neurocomputing1614
82019Macroeconomic conditions and Internet search for end-of-life care: An analysis using Google TrendsWu, P.-Y.; Wang, H.-W.; PEI-YUAN WU Taiwan Journal of Public Health00
92017Privacy-preserving PCA on horizontally-partitioned dataM. Al-Rubaie; P. Y. Wu; J. M. Chang; S. Y. Kung; PEI-YUAN WU 2017 IEEE Conference on Dependable and Secure Computing
102017Privacy-preserving PCA on horizontally-partitioned data.Al-Rubaie, Mohammad; Wu, Pei Yuan; Chang, J. Morris; Kung, Sun-Yuan; PEI-YUAN WU IEEE Conference on Dependable and Secure Computing, DSC 2017, Taipei, Taiwan, August 7-10, 2017150
112017Photolithography tool and method thereofChia-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; PEI-YUAN WU 
122017Collaborative PCA/DCA Learning Methods for Compressive PrivacyS. Y. Kung; Thee Chanyaswad; J. Morris Chang; ?P. Y. Wu; PEI-YUAN WU ACM Transactions on Embedded Computing Systems1611
132016Cost-Effective Kernel Ridge Regression Implementation for Keystroke-Based Active Authentication SystemP. Y. Wu; C. C. Fang; J. M. Chang; S. Y. Kung; PEI-YUAN WU IEEE Transactions on Cybernetics3230
142014Cost-Effective Kernel Ridge Regression for Keystroke-Based Active Authentication SystemP. Y. Wu; C. C. Fang; J. M. Chang; S. Gilbert; S. Y. Kung; PEI-YUAN WU ICASSP
152014Cost-effective kernel ridge regression implementation for keystroke-based active authentication system.Wu, Pei Yuan; Fang, Chi-Chen; Chang, J. Morris; Gilbert, Stephen B.; Kung, Sun-Yuan; PEI-YUAN WU IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 201440
162014Using Density Invariant Graph Laplacian to Resolve Unobservable Parameters for Three-Dimensional Optical Bio-ImagingC. H. Lu and?P. Y. Wu; PEI-YUAN WU International Conf. Acoustic, Speech, Signal Proc. (ICASSP)00
172014A Partial Cosine Kernel Approach to Incomplete Data AnalysisS. Y. Kung and?P. Y. Wu; PEI-YUAN WU International Conf. on Advances in Big Data Analysis (ABDA)
182013Capturing Cognitive Fingerprints from Keystroke DynamicsJ. 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; PEI-YUAN WU IT Professional1815
192012On efficient learning and classification kernel methods.Kung, Sun-Yuan; Wu, Pei Yuan; PEI-YUAN WU 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012, Kyoto, Japan, March 25-30, 2012110
202012On Efficient Learning and Classification Kernel MethodsS. Y. Kung and?P. Y. Wu; PEI-YUAN WU ICASSP
212012Perturbation Regulated Kernel Regressors for Supervised Machine LearningS. Y. Kung and?P. Y. Wu; PEI-YUAN WU International Workshop on Machine Learning for Signal Processing (MLSP)10
222011Numerical ranges as circular discs.PEI-YUAN WU Appl. Math. Lett.
232000Polygons and Numerical Ranges.PEI-YUAN WU The American Mathematical Monthly