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ORCIDYingjie Tian 0001
Ying-jie Tian 0001 – Ying-Jie Tian 0001 – Ying Jie Tian 0001
Person information
- affiliation: University of Chinese Academy of Sciences, School of Economics and Management, Beijing, China
- affiliation (PhD): China Agricultural University, Beijing, China
Other persons with the same name
- Yingjie Tian 0002
![[0000-0002-4655-6990]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-4655-6990")
— Shanghai Electric Power Research Institute, China - Yingjie Tian 0003 — Wuhan University, LIEMARS, China
- Yingjie Tian 0004 — University of South China, School of Computer Sciences, Hengyang, China
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2020 – today
- 2024
[j136]Yiqi Wang, Yingjie Tian:
Exploiting multi-scale contextual prompt learning for zero-shot semantic segmentation. Displays 81: 102616 (2024)- [j135]Yingjie Tian, Duo Su, Shilin Li:
Adaptive robust loss for landmark detection. Inf. Fusion 101: 102013 (2024) - [j134]Yingjie Tian, Yuhao Xie:
Artificial cheerleading in IEO: Marketing campaign or pump and dump scheme. Inf. Process. Manag. 61(1): 103537 (2024) - [j133]Fenfen Zhou, Yingjie Tian, Siyu Zhu:
Deep image matting with cross-layer contextual information propagation. Neural Comput. Appl. 36(12): 6809-6825 (2024) - [j132]Haoran Jiang, Zhihao Sun, Yingjie Tian:
ComCo: Complementary supervised contrastive learning for complementary label learning. Neural Networks 169: 44-56 (2024) - [j131]Xiaotong Yu, Shiding Sun, Yingjie Tian:
Self-distillation and self-supervision for partial label learning. Pattern Recognit. 146: 110016 (2024) - [j130]Kai Li, Jie Yang, Siwei Ma, Bo Wang, Shanshe Wang, Yingjie Tian, Zhiquan Qi:
Rethinking Lightweight Convolutional Neural Networks for Efficient and High-Quality Pavement Crack Detection. IEEE Trans. Intell. Transp. Syst. 25(1): 237-250 (2024) - [c76]Haoran Jiang, Zhihao Sun, Yingjie Tian:
Navigating Real-World Partial Label Learning: Unveiling Fine-Grained Images with Attributes. AAAI 2024: 12874-12882 - 2023
- [j129]Yue Wu, Wayne Wei Huang, Lean Yu, Yingjie Tian:
Group Recommendation Based on Heterogeneous Graph Algorithm for EBSNs. IEEE Access 11: 1854-1866 (2023) - [j128]Shiding Sun, Yingjie Tian, Zhiquan Qi, Yang Wu, Weizhi Gao, Yahe Wu:
Two-stage training strategy combined with neural network for segmentation of internal mammary artery graft. Biomed. Signal Process. Control. 80(Part): 104278 (2023) - [j127]Saiji Fu, Yingjie Tian, Long Tang:
Robust regression under the general framework of bounded loss functions. Eur. J. Oper. Res. 310(3): 1325-1339 (2023) - [j126]Yingjie Tian, Xiaoxi Zhao, Saiji Fu:
Kernel methods with asymmetric and robust loss function. Expert Syst. Appl. 213(Part): 119236 (2023) - [j125]Jingjing Tang, Hao He, Saiji Fu, Yingjie Tian, Gang Kou, Shan Xu:
Robust multi-view learning with the bounded LINEX loss. Neurocomputing 518: 384-400 (2023) - [j124]Saiji Fu, Yingjie Tian, Jingjing Tang, Xiaohui Liu:
Cost-sensitive learning with modified Stein loss function. Neurocomputing 525: 57-75 (2023) - [j123]Jingjing Tang, Zhaojie Hou, Xiaotong Yu, Saiji Fu, Yingjie Tian:
Multi-view cost-sensitive kernel learning for imbalanced classification problem. Neurocomputing 552: 126562 (2023) - [j122]Yingjie Tian, Weizhi Gao, Qin Zhang, Pu Sun, Dongkuan Xu:
Improving long-tailed classification by disentangled variance transfer. Internet Things 21: 100687 (2023) - [j121]Saiji Fu, Xiaoxiao Wang, Yingjie Tian, Tianyi Dong, Jingjing Tang, Jicai Li:
Coarse-grained privileged learning for classification. Inf. Process. Manag. 60(6): 103506 (2023) - [j120]Yingjie Tian, Xiaotong Yu, Saiji Fu:
Multi-view side information-incorporated tensor completion. Numer. Linear Algebra Appl. 30(5) (2023) - [j119]Yingjie Tian, Xiaotong Yu, Saiji Fu:
Partial label learning: Taxonomy, analysis and outlook. Neural Networks 161: 708-734 (2023) - [j118]Yuqi Zhang, Yingjie Tian, Junjie Hou:
CSAST: Content self-supervised and style contrastive learning for arbitrary style transfer. Neural Networks 164: 146-155 (2023) - [j117]Long Tang, Ying-Jie Tian, Xiaowei Wang, Panos M. Pardalos:
A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition. Neural Networks 166: 379-395 (2023) - [j116]Yingjie Tian, Kunlong Bai, Xiaotong Yu, Siyu Zhu:
Causal multi-label learning for image classification. Neural Networks 167: 626-637 (2023) - [j115]Siyu Zhu, Yingjie Tian:
Shape robustness in style enhanced cross domain semantic segmentation. Pattern Recognit. 135: 109143 (2023) - [j114]Shiding Sun, Xiaotong Yu, Yingjie Tian:
Multi-view prototype-based disambiguation for partial label learning. Pattern Recognit. 141: 109625 (2023) - [j113]Ming Chen, Yuqi Zhang, Saiji Fu, Yingjie Tian:
Analysis of investment effect in Xinjiang from the perspective of nontraditional security. Pers. Ubiquitous Comput. 27(4): 1573-1583 (2023) - [j112]Jiabin Liu, Hanyuan Hang, Bo Wang, Biao Li, Huadong Wang, Yingjie Tian, Yong Shi:
GAN-CL: Generative Adversarial Networks for Learning From Complementary Labels. IEEE Trans. Cybern. 53(1): 236-247 (2023) - [j111]Kai Li, Bo Wang, Yingjie Tian, Zhiquan Qi:
Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function. IEEE Trans. Cybern. 53(2): 1051-1062 (2023) - [j110]Jiabin Liu, Bo Wang, Hanyuan Hang, Huadong Wang, Zhiquan Qi, Yingjie Tian, Yong Shi:
LLP-GAN: A GAN-Based Algorithm for Learning From Label Proportions. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8377-8388 (2023) - 2022
- [j109]Yingjie Tian, Yurong Ding, Saiji Fu, Dalian Liu:
Data Boundary and Data Pricing Based on the Shapley Value. IEEE Access 10: 14288-14300 (2022) - [j108]Yiqiong Wu, Wei Huang, Yingjie Tian, Qing Zhu, Lean Yu:
An uncertainty-oriented cost-sensitive credit scoring framework with multi-objective feature selection. Electron. Commer. Res. Appl. 53: 101155 (2022) - [j107]Jingjing Tang, Dewei Li, Yingjie Tian:
Image classification with multi-view multi-instance metric learning. Expert Syst. Appl. 189: 116117 (2022) - [j106]Yingjie Tian, Shiding Sun, Zhiquan Qi, Ying Liu, Zeyuan Wang:
Non-tumorous facial pigmentation classification based on multi-view convolutional neural network with attention mechanism. Neurocomputing 483: 370-385 (2022) - [j105]Yingjie Tian, Xiaoxi Zhao, Wei Huang:
Meta-learning approaches for learning-to-learn in deep learning: A survey. Neurocomputing 494: 203-223 (2022) - [j104]Yingjie Tian, Duo Su, Stanislao Lauria, Xiaohui Liu:
Recent advances on loss functions in deep learning for computer vision. Neurocomputing 497: 129-158 (2022) - [j103]Yingjie Tian, Yuqi Zhang:
A comprehensive survey on regularization strategies in machine learning. Inf. Fusion 80: 146-166 (2022) - [j102]Saiji Fu, Xiaotong Yu, Yingjie Tian:
Cost sensitive ν-support vector machine with LINEX loss. Inf. Process. Manag. 59(2): 102809 (2022) - [j101]Xiaoxi Zhao, Saiji Fu, Yingjie Tian, Kun Zhao:
Asymmetric and robust loss function driven least squares support vector machine. Knowl. Based Syst. 258: 109990 (2022) - [j100]Yingjie Tian, Shiding Sun, Jingjing Tang:
Multi-view Teacher-Student Network. Neural Networks 146: 69-84 (2022) - [j99]Jiabin Liu, Zhiquan Qi, Bo Wang, Yingjie Tian, Yong Shi:
SELF-LLP: Self-supervised learning from label proportions with self-ensemble. Pattern Recognit. 129: 108767 (2022) - [j98]Yingjie Tian, Siyu Zhu:
Partial Domain Adaptation on Semantic Segmentation. IEEE Trans. Circuits Syst. Video Technol. 32(6): 3798-3809 (2022) - [c75]Xiang Gao, Yuqi Zhang, Yingjie Tian:
Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization. ICML 2022: 7183-7207 - [e8]Yubin Liu, Yong Shi, Yong Wang, Daji Ergu, Daniel Berg, James M. Tien, Jianping Li, Yingjie Tian:
Proceedings of the 8th International Conference on Information Technology and Quantitative Management, ITQM 2020 & 2021, Developing Global Digital Economy after COVID-19, July 9-11, 2021, Chengdu, China. Procedia Computer Science 199, Elsevier 2022 [contents] - [i10]Xiang Gao, Yingjie Tian:
Multi-view Feature Augmentation with Adaptive Class Activation Mapping. CoRR abs/2206.12943 (2022) - [i9]Xiang Gao, Yuqi Zhang, Yingjie Tian:
Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization. CoRR abs/2208.01587 (2022) - 2021
- [j97]Jingjing Tang, Yiwei He, Yingjie Tian, Dalian Liu, Gang Kou, Fawaz E. Alsaadi:
Coupling loss and self-used privileged information guided multi-view transfer learning. Inf. Sci. 551: 245-269 (2021) - [j96]Yingjie Tian, Saiji Fu, Jingjing Tang:
Incomplete-view oriented kernel learning method with generalization error bound. Inf. Sci. 581: 951-977 (2021) - [j95]Long Tang, Yingjie Tian, Wenjun Li, Panos M. Pardalos:
Valley-loss regular simplex support vector machine for robust multiclass classification. Knowl. Based Syst. 216: 106801 (2021) - [j94]Jingjing Tang, Weiqi Xu, Jiahui Li, Yingjie Tian, Shan Xu:
Multi-view learning methods with the LINEX loss for pattern classification. Knowl. Based Syst. 228: 107285 (2021) - [j93]Jingjing Tang, Jiahui Li, Weiqi Xu, Yingjie Tian, Xuchan Ju, Jie Zhang:
Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation. Neural Networks 143: 327-344 (2021) - [j92]Fenfen Zhou, Yingjie Tian, Zhiquan Qi:
Attention Transfer Network for Nature Image Matting. IEEE Trans. Circuits Syst. Video Technol. 31(6): 2192-2205 (2021) - [c74]Xiang Gao, Yingjie Tian, Zhiquan Qi:
Multi-view Feature Augmentation with Adaptive Class Activation Mapping. IJCAI 2021: 678-684 - [c73]Jiabin Liu, Bo Wang, Xin Shen, Zhiquan Qi, Yingjie Tian:
Two-stage Training for Learning from Label Proportions. IJCAI 2021: 2737-2743 - [c72]Yuqi Zhang, Duo Su, Xiaoxi Zhao, Yingjie Tian:
Sparse Multiple Instance Learning for Elderly People Balance Ability. ITQM 2021: 621-628 - [i8]Jiabin Liu, Bo Wang, Xin Shen, Zhiquan Qi, Yingjie Tian:
Two-stage Training for Learning from Label Proportions. CoRR abs/2105.10635 (2021) - [i7]Kai Li, Bo Wang, Yingjie Tian, Zhiquan Qi:
Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function. CoRR abs/2106.15510 (2021) - [i6]Kai Li, Yingjie Tian, Zhiquan Qi:
CarNet: A Lightweight and Efficient Encoder-Decoder Architecture for High-quality Road Crack Detection. CoRR abs/2109.05707 (2021) - 2020
- [j91]Yue Ma, Kun Zhao, Qi Wang, Yingjie Tian:
Incremental Cost-Sensitive Support Vector Machine With Linear-Exponential Loss. IEEE Access 8: 149899-149914 (2020) - [j90]Zhiwang Zhang, Guangxia Gao, Tao Yao, Jing He, Yingjie Tian:
An interpretable regression approach based on bi-sparse optimization. Appl. Intell. 50(11): 4117-4142 (2020) - [j89]Long Tang, Yingjie Tian, Wenjun Li, Panos M. Pardalos:
Structural improved regular simplex support vector machine for multiclass classification. Appl. Soft Comput. 91: 106235 (2020) - [j88]Yuqi Zhang, Haibin Zhang, Yingjie Tian:
Sparse multiple instance learning with non-convex penalty. Neurocomputing 391: 142-156 (2020) - [j87]Yingjie Tian, Mahboubeh Mirzabagheri, Peyman Tirandazi, Seyed Mojtaba Hosseini Bamakan:
A non-convex semi-supervised approach to opinion spam detection by ramp-one class SVM. Inf. Process. Manag. 57(6): 102381 (2020) - [j86]Yingjie Tian, Saiji Fu:
A descriptive framework for the field of deep learning applications in medical images. Knowl. Based Syst. 210: 106445 (2020) - [j85]Guoqiang Wu, Ruobing Zheng, Yingjie Tian, Dalian Liu:
Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification. Neural Networks 122: 24-39 (2020) - [j84]Yong Shi, Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian:
Deep learning from label proportions with labeled samples. Neural Networks 128: 73-81 (2020) - [j83]Wen Long, Linqiu Song, Ying-jie Tian, Wenning Yang:
Analysis of slump and surge phenomenon in Chinese stock market based on sequence alignment method. Soft Comput. 24(23): 18185-18202 (2020) - [j82]Yingjie Tian, Yiqi Wang, LinRui Yang, Zhiquan Qi:
CANet: Concatenated Attention Neural Network for Image Restoration. IEEE Signal Process. Lett. 27: 1615-1619 (2020) - [j81]Zhiquan Qi, Yingjie Tian, Yong Shi, Vassil Alexandrov:
Parallel RMCLP Classification Algorithm and Its Application on the Medical Data. IEEE Trans. Cloud Comput. 8(2): 532-538 (2020) - [j80]Xiang Gao, Yingjie Tian, Zhiquan Qi:
RPD-GAN: Learning to Draw Realistic Paintings With Generative Adversarial Network. IEEE Trans. Image Process. 29: 8706-8720 (2020) - [i5]Yingjie Tian, Yiqi Wang, LinRui Yang, Zhiquan Qi:
Concatenated Attention Neural Network for Image Restoration. CoRR abs/2006.11162 (2020)
2010 – 2019
- 2019
- [j79]Jia Wu, Shirui Pan, Junjun Jiang, Zhihua Cai, Bo Du, Yingjie Tian, Shuaiqiang Wang, Haishuai Wang:
IEEE Access Special Section Editorial: Advanced Data Analytics for Large-Scale Complex Data Environments. IEEE Access 7: 33778-33786 (2019) - [j78]Yue Ma, Qin Zhang, Dewei Li, Yingjie Tian:
LINEX Support Vector Machine for Large-Scale Classification. IEEE Access 7: 70319-70331 (2019) - [j77]Chunhua Zhang, Shiding Sun, Yingjie Tian, Zeyuan Wang:
Structured Output Prediction Using Privileged Information. IEEE Access 7: 106065-106074 (2019) - [j76]Qi Wang, Yingjie Tian, Dalian Liu:
Adaptive FH-SVM for Imbalanced Classification. IEEE Access 7: 130410-130422 (2019) - [j75]Zhiwang Zhang, Jing He, Guangxia Gao, Yingjie Tian:
Bi-sparse optimization-based least squares regression. Appl. Soft Comput. 77: 300-315 (2019) - [j74]Wen Long, Linqiu Song, Ying-jie Tian:
A new graphic kernel method of stock price trend prediction based on financial news semantic and structural similarity. Expert Syst. Appl. 118: 411-424 (2019) - [j73]Yiwei He, Yingjie Tian, Dalian Liu:
Multi-view transfer learning with privileged learning framework. Neurocomputing 335: 131-142 (2019) - [j72]Jiashuai Zhang, Jianyu Miao, Kun Zhao, Yingjie Tian:
Multi-task feature selection with sparse regularization to extract common and task-specific features. Neurocomputing 340: 76-89 (2019) - [j71]Long Tang, Yingjie Tian, Panos M. Pardalos:
A novel perspective on multiclass classification: Regular simplex support vector machine. Inf. Sci. 480: 324-338 (2019) - [j70]Jingjing Tang, Yingjie Tian, Dalian Liu, Gang Kou:
Coupling privileged kernel method for multi-view learning. Inf. Sci. 481: 110-127 (2019) - [j69]Dandan Chen, Yingjie Tian:
Large-scale structural learning and predicting via hashing approximation. Neural Comput. Appl. 31(7): 2889-2903 (2019) - [j68]Jingjing Tang, Yingjie Tian, Xiaohui Liu:
LGND: a new method for multi-class novelty detection. Neural Comput. Appl. 31(8): 3339-3355 (2019) - [j67]Zhiwang Zhang, Jing He, Guangxia Gao, Yingjie Tian:
Sparse multi-criteria optimization classifier for credit risk evaluation. Soft Comput. 23(9): 3053-3066 (2019) - [c71]Zhichen Lu, Wen Long, Jiashuai Zhang, Yingjie Tian:
Factor Integration Based on Neural Networks for Factor Investing. ICCS (3) 2019: 286-292 - [c70]Yuting Niu, Yuan Shang, Yingjie Tian:
Multi-view SVM Classification with Feature Selection. ITQM 2019: 405-412 - [c69]Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian, Yong Shi:
Learning from Label Proportions with Generative Adversarial Networks. NeurIPS 2019: 7167-7177 - [i4]Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian, Yong Shi:
Learning from Label Proportions with Generative Adversarial Networks. CoRR abs/1909.02180 (2019) - [i3]Guoqiang Wu, Ruobing Zheng, Yingjie Tian, Dalian Liu:
Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification. CoRR abs/1911.01658 (2019) - 2018
- [j66]Yiwei He, Yingjie Tian, Jingjing Tang, Yue Ma:
Unsupervised Domain Adaptation Using Exemplar-SVMs with Adaptation Regularization. Complex. 2018: 8425821:1-8425821:13 (2018) - [j65]Guoqiang Wu, Yingjie Tian, Chunhua Zhang:
A unified framework implementing linear binary relevance for multi-label learning. Neurocomputing 289: 86-100 (2018) - [j64]Yingjie Tian, Mahboubeh Mirzabagheri, Seyed Mojtaba Hosseini Bamakan, Huadong Wang, Qiang Qu:
Ramp loss one-class support vector machine; A robust and effective approach to anomaly detection problems. Neurocomputing 310: 223-235 (2018) - [j63]Long Tang, Yingjie Tian, Chunyan Yang, Panos M. Pardalos:
Ramp-loss nonparallel support vector regression: Robust, sparse and scalable approximation. Knowl. Based Syst. 147: 55-67 (2018) - [j62]Jingjing Tang, Dewei Li, Yingjie Tian, Dalian Liu:
Multi-view learning based on nonparallel support vector machine. Knowl. Based Syst. 158: 94-108 (2018) - [j61]Xuchan Ju, Yingjie Tian:
A divide-and-conquer method for large scale ν-nonparallel support vector machines. Neural Comput. Appl. 29(9): 497-509 (2018) - [j60]Fan Meng, Zhiquan Qi, Yingjie Tian, Lingfeng Niu:
Pedestrian detection based on the privileged information. Neural Comput. Appl. 29(12): 1485-1494 (2018) - [j59]Wen Long, Ye-ran Tang, Ying-jie Tian:
Investor sentiment identification based on the universum SVM. Neural Comput. Appl. 30(2): 661-670 (2018) - [j58]Dewei Li, Yingjie Tian:
Improved least squares support vector machine based on metric learning. Neural Comput. Appl. 30(7): 2205-2215 (2018) - [j57]Long Tang, Yingjie Tian, Chunyan Yang:
Nonparallel support vector regression model and its SMO-type solver. Neural Networks 105: 431-446 (2018) - [j56]Dewei Li, Yingjie Tian:
Survey and experimental study on metric learning methods. Neural Networks 105: 447-462 (2018) - [j55]Jingjing Tang, Yingjie Tian, Xiaohui Liu, Dewei Li, Jia Lv, Gang Kou:
Improved multi-view privileged support vector machine. Neural Networks 106: 96-109 (2018) - [j54]Guoqiang Wu, Yingjie Tian, Dalian Liu:
Cost-sensitive multi-label learning with positive and negative label pairwise correlations. Neural Networks 108: 411-423 (2018) - [j53]Dalian Liu, Dewei Li, Yong Shi, Yingjie Tian:
Large-scale linear nonparallel SVMs. Soft Comput. 22(6): 1945-1957 (2018) - [j52]Jingjing Tang, Yingjie Tian, Peng Zhang, Xiaohui Liu:
Multiview Privileged Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3463-3477 (2018) - [j51]Zhiquan Qi, Fan Meng, Yingjie Tian, Lingfeng Niu, Yong Shi, Peng Zhang:
Adaboost-LLP: A Boosting Method for Learning With Label Proportions. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3548-3559 (2018) - [c68]Shiding Sun, Chunhua Zhang, Yingjie Tian:
A New Method for Structured Learning with Privileged Information. ICCS (2) 2018: 453-461 - [c67]Guoqiang Wu, Yingjie Tian, Dalian Liu:
Privileged Multi-Target Support Vector Regression. ICPR 2018: 385-390 - [c66]Jingjing Tang, Yingjie Tian, Dalian Liu:
Large-Scale Linear NPSVM via One Permutation Hashing. IJCNN 2018: 1-8 - [c65]Yue Ma, Yiwei He, Yingjie Tian:
Online Robust Lagrangian Support Vector Machine against Adversarial Attack. ITQM 2018: 173-181 - [e7]Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack J. Dongarra, Peter M. A. Sloot:
Computational Science - ICCS 2018 - 18th International Conference, Wuxi, China, June 11-13, 2018, Proceedings, Part I. Lecture Notes in Computer Science 10860, Springer 2018, ISBN 978-3-319-93697-0 [contents] - [e6]Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack J. Dongarra, Peter M. A. Sloot:
Computational Science - ICCS 2018 - 18th International Conference, Wuxi, China, June 11-13, 2018, Proceedings, Part II. Lecture Notes in Computer Science 10861, Springer 2018, ISBN 978-3-319-93700-7 [contents] - [e5]Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack J. Dongarra, Peter M. A. Sloot:
Computational Science - ICCS 2018 - 18th International Conference, Wuxi, China, June 11-13, 2018 Proceedings, Part III. Lecture Notes in Computer Science 10862, Springer 2018, ISBN 978-3-319-93712-0 [contents] - [e4]Yong Shi, Peter Wolcott, Wikil Kwak, Zhengxin Chen, Yingjie Tian, Heeseok Lee:
Proceedings of the 6th International Conference on Information Technology and Quantitative Management, ITQM 2018, Advanced Information Technology and Global Business Competition, October 20-21, 2018, Omaha, Nebraska, USA. Procedia Computer Science 139, Elsevier 2018 [contents] - 2017
- [j50]Jingjing Tang, Yingjie Tian:
A multi-kernel framework with nonparallel support vector machine. Neurocomputing 266: 226-238 (2017) - [j49]Dewei Li, Yingjie Tian:
Global and local metric learning via eigenvectors. Knowl. Based Syst. 116: 152-162 (2017) - [j48]Xin Shen, Lingfeng Niu, Zhiquan Qi, Yingjie Tian:
Support vector machine classifier with truncated pinball loss. Pattern Recognit. 68: 199-210 (2017) - [j47]Yuan Ping, Yingjie Tian, Chun Guo, Baocang Wang, Yuehua Yang:
FRSVC: Towards making support vector clustering consume less. Pattern Recognit. 69: 286-298 (2017) - [j46]Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian, Xingquan Zhu, Xindong Wu:
SALE: Self-adaptive LSH encoding for multi-instance learning. Pattern Recognit. 71: 460-482 (2017) - [j45]Lingfeng Niu, Ruizhi Zhou, Yingjie Tian, Zhiquan Qi, Peng Zhang:
Nonsmooth Penalized Clustering via ℓp Regularized Sparse Regression. IEEE Trans. Cybern. 47(6): 1423-1433 (2017) - [j44]Huadong Wang, Yong Shi, Lingfeng Niu, Yingjie Tian:
Nonparallel Support Vector Ordinal Regression. IEEE Trans. Cybern. 47(10): 3306-3317 (2017) - [c64]Dewei Li, Jingjing Tang, Yingjie Tian, Xuchan Ju:
Multi-view deep metric learning for image classification. ICIP 2017: 4142-4146 - [c63]Dewei Li, Dongkuan Xu, Jingjing Tang, Yingjie Tian:
Metric learning for multi-instance classification with collapsed bags. IJCNN 2017: 372-379 - [c62]Jingjing Tang, Yingjie Tian, Guoqiang Wu, Dewei Li:
Stochastic gradient descent for large-scale linear nonparallel SVM. WI 2017: 980-983 - [e3]Vandana Ahuja, Yong Shi, Deepak Khazanchi, Naseem Abidi, Yingjie Tian, Daniel Berg, James M. Tien:
Proceedings of the 5th International Conference on Information Technology and Quantitative Management, ITQM 2017, Creating Knowledge and Wisdom via Big Data Analytics, December 8-10, 2017, New Delhi, India. Procedia Computer Science 122, Elsevier 2017 [contents] - 2016
- [j43]Yingjie Tian, Ying Zhang, Dalian Liu:
Semi-supervised support vector classification with self-constructed Universum. Neurocomputing 189: 33-42 (2016) - [j42]Seyed Mojtaba Hosseini Bamakan, Huadong Wang, Yingjie Tian, Yong Shi:
An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization. Neurocomputing 199: 90-102 (2016) - [j41]Zhiwang Zhang, Guangxia Gao, Yingjie Tian, Jue Yue:
Two-phase multi-kernel LP-SVR for feature sparsification and forecasting. Neurocomputing 214: 594-606 (2016) - [j40]Dalian Liu, Yong Shi, Yingjie Tian, Xiankai Huang:
Ramp loss least squares support vector machine. J. Comput. Sci. 14: 61-68 (2016) - [j39]Zhiquan Qi, Bo Wang, Yingjie Tian, Peng Zhang:
When Ensemble Learning Meets Deep Learning: a New Deep Support Vector Machine for Classification. Knowl. Based Syst. 107: 54-60 (2016) - [j38]Yingjie Tian, Xuchan Ju, Yong Shi:
A divide-and-combine method for large scale nonparallel support vector machines. Neural Networks 75: 12-21 (2016) - [j37]Dandan Chen, Yingjie Tian, Xiaohui Liu:
Structural nonparallel support vector machine for pattern recognition. Pattern Recognit. 60: 296-305 (2016) - [c61]Dalian Liu, Dandan Chen, Yong Shi, Yingjie Tian:
Ramp Loss Linear Programming Nonparallel Support Vector Machine. ICCS 2016: 1745-1754 - [c60]Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian, Chengqi Zhang:
Unsupervised Feature Learning from Time Series. IJCAI 2016: 2322-2328 - [c59]Dandan Chen, Yingjie Tian:
v-Structural Nonparallel Support Vector Machine for Pattern Classification. WI Workshops 2016: 33-36 - [i2]Dewei Li, Yingjie Tian:
Multi-view metric learning for multi-instance image classification. CoRR abs/1610.06671 (2016) - [i1]Dongkuan Xu, Jia Wu, Wei Zhang, Yingjie Tian:
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning. CoRR abs/1612.03550 (2016) - 2015
- [j36]Xiuzhen Cheng, Yunchuan Sun, Antonio J. Jara, Houbing Song, Yingjie Tian:
Big Data and Knowledge Extraction for Cyber-Physical Systems. Int. J. Distributed Sens. Networks 11: 231527:1-231527:4 (2015) - [j35]Xingsen Li, Yingjie Tian, Florentin Smarandache, Rajan Alex:
An Extension Collaborative Innovation Model in the Context of Big Data. Int. J. Inf. Technol. Decis. Mak. 14(1): 69-92 (2015) - [j34]Dewei Li, Yingjie Tian:
Twin support vector machine in linear programs. J. Comput. Sci. 10: 270-277 (2015) - [j33]Yuan Ping, Yun Feng Chang, Yajian Zhou, Yingjie Tian, Yixian Yang, Zhili Zhang:
Fast and scalable support vector clustering for large-scale data analysis. Knowl. Inf. Syst. 43(2): 281-310 (2015) - [j32]Dalian Liu, Yong Shi, Yingjie Tian:
Ramp loss nonparallel support vector machine for pattern classification. Knowl. Based Syst. 85: 224-233 (2015) - [j31]Zhiwang Zhang, Guangxia Gao, Yingjie Tian:
Multi-kernel multi-criteria optimization classifier with fuzzification and penalty factors for predicting biological activity. Knowl. Based Syst. 89: 301-313 (2015) - [j30]Zhiquan Qi, Yingjie Tian, Lingfeng Niu, Bo Wang:
Semi-supervised classification with privileged information. Int. J. Mach. Learn. Cybern. 6(4): 667-676 (2015) - [j29]Zhiquan Qi, Yingjie Tian, Yong Shi:
Successive Overrelaxation for Laplacian Support Vector Machine. IEEE Trans. Neural Networks Learn. Syst. 26(4): 674-683 (2015) - [c58]Jingjing Tang, Yingjie Tian, Dalian Liu:
Connected bit minwise hashing for large-scale linear SVM. FSKD 2015: 995-1002 - [c57]Xuchan Ju, Yingjie Tian, Dalian Liu, Zhiquan Qi:
Nonparallel Hyperplanes Support Vector Machine for Multi-class Classification. ICCS 2015: 1574-1582 - [c56]Xin Shen, Lingfeng Niu, Yingjie Tian, Yong Shi:
Alternating Direction Method of Multipliers for Nonparallel Support Vector Machines. ICDM Workshops 2015: 1171-1176 - [c55]Zhiquan Qi, Yingjie Tian, Lingfeng Niu, Fan Meng, Limeng Cui, Yong Shi:
Pedestrian Detection Using Privileged Information. ICDM Workshops 2015: 1185-1188 - [c54]Xuchan Ju, Yingjie Tian, Dalian Liu, Manjin Cheng, Yuhong Xia, Fuqiang Quo:
Multi-Dimensional Critical Control of Water Resource in Bayannur. ITQM 2015: 238-245 - [c53]Jingjing Tang, Yingjie Tian:
f-Fractional Bit Minwise Hashing for Large-Scale Learning. WI-IAT (3) 2015: 60-63 - [e2]Chengqi Zhang, Wei Huang, Yong Shi, Philip S. Yu, Yangyong Zhu, Yingjie Tian, Peng Zhang, Jing He:
Data Science - Second International Conference, ICDS 2015 Sydney, Australia, August 8-9, 2015. Proceedings. Lecture Notes in Computer Science 9208, Springer 2015, ISBN 978-3-319-24473-0 [contents] - 2014
- [j28]Zhiquan Qi, Yingjie Tian, Xiaodan Yu, Yong Shi:
A multi-instance learning algorithm based on nonparallel classifier. Appl. Math. Comput. 241: 233-241 (2014) - [j27]Yunchuan Sun, Hongli Yan, Junsheng Zhang, Ye Xia, Shenling Wang, Rongfang Bie, Yingjie Tian:
Organizing and Querying the Big Sensing Data with Event-Linked Network in the Internet of Things. Int. J. Distributed Sens. Networks 10 (2014) - [j26]Zhiquan Qi, Yingjie Tian, Yong Shi:
A new classification model using privileged information and its application. Neurocomputing 129: 146-152 (2014) - [j25]Yingjie Tian, Qin Zhang, Yuan Ping:
Large-scale linear nonparallel support vector machine solver. Neurocomputing 138: 114-119 (2014) - [j24]Zhiquan Qi, Yingjie Tian, Yong Shi:
A nonparallel support vector machine for a classification problem with universum learning. J. Comput. Appl. Math. 263: 288-298 (2014) - [j23]Zhiquan Qi, Yingjie Tian, Yong Shi:
Regularized multiple-criteria linear programming with universum and its application. Neural Comput. Appl. 24(3-4): 621-628 (2014) - [j22]Yingjie Tian, Xuchan Ju, Zhiquan Qi:
Efficient sparse nonparallel support vector machines for classification. Neural Comput. Appl. 24(5): 1089-1099 (2014) - [j21]Yingjie Tian, Qin Zhang, Dalian Liu:
ν-Nonparallel support vector machine for pattern classification. Neural Comput. Appl. 25(5): 1007-1020 (2014) - [j20]Yingjie Tian, Yuan Ping:
Large-scale linear nonparallel support vector machine solver. Neural Networks 50: 166-174 (2014) - [j19]Dalian Liu, Yingjie Tian, Rongfang Bie, Yong Shi:
Self-Universum support vector machine. Pers. Ubiquitous Comput. 18(8): 1813-1819 (2014) - [j18]Yingjie Tian, Zhiquan Qi, Xuchan Ju, Yong Shi, Xiaohui Liu:
Nonparallel Support Vector Machines for Pattern Classification. IEEE Trans. Cybern. 44(7): 1067-1079 (2014) - [c52]Dewei Li, Yingjie Tian:
Twin Support Vector Machine in Linear Programs. ICCS 2014: 1770-1778 - [c51]Dewei Li, Yingjie Tian, Honggui Xu:
Deep Twin Support Vector Machine. ICDM Workshops 2014: 65-73 - [c50]Ying Zhang, Yingjie Tian, Zhiquan Qi:
Biased Support Vector Machine with Self-Constructed Universum for PU Learning. ICDM Workshops 2014: 93-100 - [c49]Ying Zhang, Xuchan Ju, Yingjie Tian:
Nonparallel hyperplane support vector machine for PU learning. ICNC 2014: 703-708 - [c48]Zhiquan Qi, Vassil Alexandrov, Yong Shi, Yingjie Tian:
Parallel Regularized Multiple-criteria Linear Programming. ITQM 2014: 58-65 - [c47]Xuchan Ju, Manjin Cheng, Yuhong Xia, Fuqiang Quo, Yingjie Tian:
Support Vector Regression and Time Series Analysis for the Forecasting of Bayannur's Total Water Requirement. ITQM 2014: 523-531 - [c46]Qin Zhang, Manjin Cheng, Yuhong Xia, Fuqiang Guo, Yingjie Tian:
Correlation Analysis for Multiple-dimensional Properties of Water Recourses. ITQM 2014: 542-551 - 2013
- [j17]Yingjie Tian, Xuchan Ju, Zhiquan Qi, Yong Shi:
Efficient sparse least squares support vector machines for pattern classification. Comput. Math. Appl. 66(10): 1935-1947 (2013) - [j16]Zhiquan Qi, Yingjie Tian, Yong Shi:
Structural twin support vector machine for classification. Knowl. Based Syst. 43: 74-81 (2013) - [j15]Zhiquan Qi, Yingjie Tian, Yong Shi:
Efficient railway tracks detection and turnouts recognition method using HOG features. Neural Comput. Appl. 23(1): 245-254 (2013) - [j14]Zhiquan Qi, Yingjie Tian, Yong Shi:
Multi-instance classification based on regularized multiple criteria linear programming. Neural Comput. Appl. 23(3-4): 857-863 (2013) - [j13]Zhiquan Qi, Yingjie Tian, Yong Shi:
Robust twin support vector machine for pattern classification. Pattern Recognit. 46(1): 305-316 (2013) - [c45]Zhiquan Qi, Yingjie Tian, Yong Shi, Xiaodan Yu:
Cost-Sensitive Support Vector Machine for Semi-Supervised Learning. ICCS 2013: 1684-1689 - [c44]Yanan Wang, Xi Zhao, Yingjie Tian:
Local and Global Regularized Twin SVM. ICCS 2013: 1710-1719 - [c43]Zhiquan Qi, Yingjie Tian, Xiaodan Yu, Yong Shi:
How to Improve the Quality of Pedestrian Detection Using the Priori Knowledge. ICDM Workshops 2013: 795-799 - [c42]Qin Zhang, Yingjie Tian, Dalian Liu:
Nonparallel Support Vector Machines for Multiple-Instance Learning. ITQM 2013: 1063-1072 - [e1]Yong Shi, Youmin Xi, Peter Wolcott, Yingjie Tian, Jianping Li, Daniel Berg, Zhengxin Chen, Enrique Herrera-Viedma, Gang Kou, Heeseok Lee, Yi Peng, Lean Yu:
Proceedings of the First International Conference on Information Technology and Quantitative Management, ITQM 2013, Dushu Lake Hotel, Sushou, China, 16-18 May, 2013. Procedia Computer Science 17, Elsevier 2013 [contents] - 2012
- [j12]Yuan Ping, Yingjie Tian, Yajian Zhou, Yixian Yang:
Convex Decomposition Based Cluster Labeling Method for Support Vector Clustering. J. Comput. Sci. Technol. 27(2): 428-442 (2012) - [j11]Zhiquan Qi, Yingjie Tian, Yong Shi:
Laplacian twin support vector machine for semi-supervised classification. Neural Networks 35: 46-53 (2012) - [j10]Zhiquan Qi, Yingjie Tian, Yong Shi:
Twin support vector machine with Universum data. Neural Networks 36: 112-119 (2012) - [c41]Yingjie Tian, Xuchan Ju, Zhiquan Qi, Yong Shi:
Efficient sparse least squares support vector machines for pattern classification. FSKD 2012: 697-701 - [c40]Zhiquan Qi, Yingjie Tian, Yong Shi:
A Simple and Fast Multi-instance Classification via Support Vector Machine. Web Intelligence/IAT Workshops 2012: 1-4 - [c39]Xu Chan Ju, Ying Jie Tian:
Efficient Implementation of Nonparallel Hyperplanes Classifier. Web Intelligence/IAT Workshops 2012: 5-9 - [c38]Zhiquan Qi, Yingjie Tian, Yong Shi:
Regular Multiple Criteria Linear Programming for Semi-supervised Classification. ICDM Workshops 2012: 500-505 - [c37]Yanan Wang, Yingjie Tian:
Fast Localized Twin SVM. ICNC 2012: 74-78 - [c36]Zhiquan Qi, Yingjie Tian, Yong Shi:
Regularized Multiple Criteria Linear Programming via Linear Programming. ICCS 2012: 1234-1239 - [c35]Xuchan Ju, Yingjie Tian:
Knowledge-based Support Vector Machine Classifiers via Nearest Points. ICCS 2012: 1240-1248 - 2011
- [b1]Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, Jianping Li:
Optimization Based Data Mining: Theory and Applications. Advanced Information and Knowledge Processing, Springer 2011, ISBN 978-0-85729-503-3, pp. 1-316 - [j9]Ruoying Chen, Wenjing Chen, Sixiao Yang, Di Wu, Yong Wang, Yingjie Tian, Yong Shi:
Rigorous assessment and integration of the sequence and structure based features to predict hot spots. BMC Bioinform. 12: 311 (2011) - [j8]Xiaofei Zhou, Wenhan Jiang, Yong Shi, Yingjie Tian:
Credit risk evaluation with kernel-based affine subspace nearest points learning method. Expert Syst. Appl. 38(4): 4272-4279 (2011) - [j7]Guangli Nie, Wei Rowe, Lingling Zhang, Yingjie Tian, Yong Shi:
Credit card churn forecasting by logistic regression and decision tree. Expert Syst. Appl. 38(12): 15273-15285 (2011) - [j6]Dongling Zhang, Yingjie Tian, Yong Shi:
A group of knowledge-incorporated multiple criteria linear programming classifiers. J. Comput. Appl. Math. 235(13): 3705-3717 (2011) - [c34]Sixiao Yang, Ying Jie Tian:
A new rule extraction approach from Support Vector Machines. FSKD 2011: 978-982 - [c33]Sixiao Yang, Ying Jie Tian, Chunhua Zhang:
Rule Extraction from Support Vector Machines and Its Applications. Web Intelligence/IAT Workshops 2011: 221-224 - [c32]Xu Chan Ju, Ying Jie Tian:
A Novel Knowledge-Based Twin Support Vector Machine. ICDM Workshops 2011: 429-433 - [c31]Yingjie Tian, Yong Shi, Xiaojun Chen, Wenjing Chen:
AUC Maximizing Support Vector Machines with Feature Selection. ICCS 2011: 1691-1698 - 2010
- [j5]Xiaofei Zhou, Wenhan Jiang, Yingjie Tian, Yong Shi:
Kernel subclass convex hull sample selection method for SVM on face recognition. Neurocomputing 73(10-12): 2234-2246 (2010) - [j4]Zhixia Yang, Yingjie Tian:
Second Order Cone Programming Formulations for Handling Data with Perturbation. J. Convergence Inf. Technol. 5(9): 267-278 (2010) - [c30]Yingjie Tian, Jun Yu, Wenjing Chen:
lp-norm support vector machine with CCCP. FSKD 2010: 1560-1564 - [c29]Zhan Zhang, Dongling Zhang, Yingjie Tian:
Kernel-based multiple criteria linear programming classifier. ICCS 2010: 2407-2415 - [c28]Wen Jing Chen, Ying Jie Tian:
Lp-norm proximal support vector machine and its applications. ICCS 2010: 2417-2423
2000 – 2009
- 2009
- [j3]Yong Shi, Yingjie Tian, Xiaojun Chen, Peng Zhang:
Regularized multiple criteria linear programs for classification. Sci. China Ser. F Inf. Sci. 52(10): 1812-1820 (2009) - [j2]Dongling Zhang, Yong Shi, Yingjie Tian, Meihong Zhu:
A class of classification and regression methods by multiobjective programming. Frontiers Comput. Sci. China 3(2): 192-204 (2009) - [j1]Zhixia Yang, Yingjie Tian, Naiyang Deng:
Leave-one-out bounds for support vector ordinal regression machine. Neural Comput. Appl. 18(7): 731-748 (2009) - [c27]Jiashu Zhou, Erping Wang, Yiwen Chen, Xuanna Wu, Yujie Ma, Yingjie Tian:
Forecasting Model of Mass Incidents in China - An Explorative Research Based on Suppport Vector Machine. BIFE 2009: 152-155 - [c26]Weibing Chen, Hongxia Yin, Yingjie Tian:
Smoothing Newton Method for L1 Soft Margin Data Classification Problem. ICCS (2) 2009: 543-551 - [c25]Guangli Nie, Guoxun Wang, Peng Zhang, Yingjie Tian, Yong Shi:
Finding the Hidden Pattern of Credit Card Holder's Churn: A Case of China. ICCS (2) 2009: 561-569 - [c24]Xiaofei Zhou, Wenhan Jiang, Yingjie Tian, Peng Zhang, Guangli Nie, Yong Shi:
A New Kernel-Based Classification Algorithm. ICDM 2009: 1094-1099 - [c23]Kun Zhao, Yingjie Tian, Naiyang Deng:
Robust Unsupervised and Semi-supervised Bounded v - Support Vector Machines. ISNN (2) 2009: 312-321 - 2008
- [c22]Dongling Zhang, Yingjie Tian, Peng Zhang:
Kernel-Based Nonparametric Regression Method. Web Intelligence/IAT Workshops 2008: 410-413 - [c21]Peng Zhang, Yingjie Tian, Zhiwang Zhang, Aihua Li, Xingquan Zhu:
Select Objective Functions for Multiple Criteria Programming Classification. Web Intelligence/IAT Workshops 2008: 420-423 - [c20]Peng Zhang, Yingjie Tian, Xingsen Li, Zhiwang Zhang, Yong Shi:
Select Representative Samples for Regularized Multiple-Criteria Linear Programming Classification. ICCS (2) 2008: 436-440 - [c19]Chuanliang Chen, Yun-Chao Gong, Yingjie Tian:
KCK-Means: A Clustering Method Based on Kernel Canonical Correlation Analysis. ICCS (1) 2008: 995-1004 - [c18]Chuanliang Chen, Yingjie Tian, Chunhua Zhang:
Spam filtering with several novel bayesian classifiers. ICPR 2008: 1-4 - [c17]Yun-Chao Gong, Chuanliang Chen, Yingjie Tian:
Graph-based semi-supervised learning with redundant views. ICPR 2008: 1-4 - [c16]Chengming Qi, Yingjie Tian, Shoumei Cui, Yunchuan Sun:
Concept Semilattice: Construction and Complexity. ICYCS 2008: 1849-1853 - [c15]Yingjie Tian, Yunchuan Sun, Chuanliang Chen, Zhan Zhang:
Unconstrained transductive Support Vector Machines and its application. IJCNN 2008: 137-141 - [c14]Yingjie Tian, Chuanliang Chen, Chunhua Zhang:
AODE for Source Code Metrics for Improved Software Maintainability. SKG 2008: 330-335 - [c13]Chuanliang Chen, Yunchao Gong, Yingjie Tian:
Semi-supervised learning methods for network intrusion detection. SMC 2008: 2603-2608 - 2007
- [c12]Yingjie Tian, Manfu Yan:
Unconstrained Transductive Support Vector Machines. FSKD (2) 2007: 181-185 - [c11]Ruxin Qin, Jing Chen, Naiyang Deng, Yingjie Tian:
A Leave-One-Out Bound for nu-Support Vector Regression. International Conference on Computational Science (3) 2007: 669-676 - [c10]Zhan Zhang, Yingjie Tian, Yong Shi:
Feature Selection for VIP E-Mail Accounts Analysis. International Conference on Computational Science (3) 2007: 693-700 - [c9]Kun Zhao, Yingjie Tian, Naiyang Deng:
Unsupervised and Semi-supervised Lagrangian Support Vector Machines. International Conference on Computational Science (3) 2007: 882-889 - [c8]Yong Shi, Yingjie Tian, Xiaojun Chen, Peng Zhang:
A Regularized Multiple Criteria Linear Program for Classification. ICDM Workshops 2007: 253-258 - [c7]Kun Zhao, Ying-Jie Tian, Naiyang Deng, Hiroshi Kuwajima, Takashi Washio:
Robust Unsupervised and Semisupervised Bounded C-Support Vector Machines. ICDM Workshops 2007: 331-336 - 2006
- [c6]Kun Zhao, Ying-Jie Tian, Naiyang Deng:
Unsupervised and Semi-Supervised Two-class Support Vector Machines. ICDM Workshops 2006: 813-817 - 2005
- [c5]Yingjie Tian, Zhiquan Qi:
A New Support Vector Machine for Multi-class Classification. CIT 2005: 18-22 - [c4]Zhixia Yang, Naiyang Deng, Yingjie Tian:
A Multi-class Classification Algorithm based on Ordinal Regression Machine. CIMCA/IAWTIC 2005: 810-815 - [c3]Yingjie Tian, Naiyang Deng:
Leave-one-out Bounds for Support Vector Regression. CIMCA/IAWTIC 2005: 1061-1066 - [c2]Zhiquan Qi, Yingjie Tian, Naiyang Deng:
A New Support Vector Machine for Multi-class Classification. CIS (1) 2005: 580-585 - [c1]Yingjie Tian, Naiyang Deng:
Support Vector Classification with Nominal Attributes. CIS (1) 2005: 586-591
Coauthor Index
[j130] [j128] [j111] [j110] [j106] [j99] [j92] [c74] [c73] [i8] [i7] [i6] [j84] [j82] [j81] [j80] [i5] [c69] [i4] [j60] [j51] [j48] [j45] [j39] [j30] [j29] [c57] [c55] [j28] [j26] [j24] [j23] [j22] [j18] [c50] [c48] [j17] [j16] [j15] [j14] [j13] [c45] [c43] [j11] [j10] [c41] [c40] [c38] [c36] [c5] [c2]
[j112] [j110] [j99] [e8] [j84] [j81] [c69] [i4] [j53] [j51] [e7] [e6] [e5] [e4] [j44] [e3] [j42] [j40] [j38] [c61] [j32] [j29] [c56] [c55] [e2] [j28] [j26] [j24] [j23] [j19] [j18] [c48] [j17] [j16] [j15] [j14] [j13] [c45] [c43] [e1] [j11] [j10] [c41] [c40] [c38] [c36] [b1] [j9] [j8] [j7] [j6] [c31] [j5] [j3] [j2] [c25] [c24] [c20] [c10] [c8]
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