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Welcome to Allan's Homepage [養天地正氣,法古今完人]
Z. Allan Ding, 丁正明

Dr. and Assistant Professor
Department of Computer, Information and Technology
Purdue School of Engineering and Technology
Indiana University-Purdue University Indianapolis
799 West Michigan St., ET 301, Indianapolis IN 46202
Email: zd2[at]iu[dot]edu
Office No.: +1(317)274-8344
About Me [Google Scholar] [Latest CV] (by Feb. 2019)

Research Interests: Transfer learning/Domain adaptation, Deep learning, and Multi-view learning.

Education: Ph.D at CE, NEU, 2018; M.Eng. at CS, UESTC, 2013; B.Eng. at CS, UESTC, 2010.

Internship: Microsoft Research (with Yandong Guo and Lei Zhang), 2017; Adobe Systems Incorporated (with William Yan), 2016; Army Research Lab (with Nasser M. Nasrabadi), 2015.

Opening Positions
I am always looking for self-motivated graduate students and visiting students/scholars. Feel free to contact me with your CV. Specifically, the Ph.D. students will receive the degree from Purdue University.

What is New!
[11/2019] We get three papers accepted by 34th AAAI Conference on Artificial Intelligence (AAAI-20) [acceptance rate: 20.6%].
[10/2019] I accept the invitation of the Program Committee (PC) for 24th European Conference on Artificial Intelligence (ECAI-20).
[09/2019] I accept the invitation of the Program Committee (PC) for IEEE Conference on Computer Vision and Pattern Recognition (CVPR-20).
[08/2019] We get one regular paper on multi-label learning accepted by IEEE International Conference on Data Mining (ICDM), 2019 [acceptance rate: 9.08%]. Congratulations to Lichen.
[07/2019] We get one oral paper on action recognition accepted by International Conference on Computer Vision (ICCV), 2019 [acceptance rate: 4.3%]. Congratulations to Lichen.
[07/2019] We get two papers on deep domain adaptation accepted by ACM International Conference on Multimedia (ACM MM), 2019.
[06/2019] I accept the invitation of the Senior Program Committee (SPC) for 34th AAAI Conference on Artificial Intelligence (AAAI-20).
[05/2019] Two PhD students (Mei Qiu and Haifeng Xia) and two visiting PhD students (Bingrong Xu and Guanglei Yang) will join us soon. Welcome to Indy.
[03/2019] We get one paper on action recognition accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). Congratulations to Chengcheng.
[03/2019] We get one paper on multi-view clustering accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Congratulations to Zhiqiang.
[03/2019] We get one paper on outlier detection accepted by IEEE Access.
[02/2019] We have two papers on zero-shot learning acepted by 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR-19). The acceptance rate is 25.2%.
[02/2019] We get one paper on Deep Decision Tree Transfer Boosting accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Congratulations to Shuhui, Haiyi.
[02/2019] We get one paper on feature learning accepted by IEEE Transactions on Image Processing (TIP). Congratulations to Shuyang.
[01/2019] I have accepted the invitation of serving Program Committee (PC) for the 28th International Joint Conference on Artificial Intelligence (IJCAI-19)

Tutorials

[T-4] Zhengming Ding, Hongfu Liu and Handong Zhao. Deep Multi-view Data Analytics, Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA
[T-3] Zhengming Ding, Ming Shao, Yun Fu. Large-Scale Multi-view Data Analysis, IEEE International Conference on Big Data, 2018, Seattle, WA, USA
[T-2] Zhengming Ding, Ming Shao, Yun Fu. Multi-view Visual Data Analytics [Slides], IEEE International Conference on Computer Vision and Pattern Recognition, 2018, Salt Lake City, USA
[T-1] Zhengming Ding, Handong Zhao, Yun Fu. Multi-view Face Representation, IEEE International Conference on Automatic Face and Gesture Recognition, 2017, Washington, DC

Selected Publications

[Full Journal Publications](3 TPAMI, 6 TNNLS, 1 TKDE, 11 TIP, 2 TCSVT, etc.)

[J-10] Zhengming Ding, Ming Shao, Wonjun Hwang, Sungjoo Suh, Jae-Joon Han, Changkyu Choi, and Yun Fu. Robust Discriminative Metric Learning for Image Representation. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), (accepted) 2018. [pdf][bib][code]
[J-9] Zhengming Ding, and Yun Fu. Deep Transfer Low-Rank Coding for Cross-Domain Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (accepted) 2018. [pdf][bib][code]
[J-8] Zhengming Ding, Ming Shao, and Yun Fu. Generative Zero-Shot Learning via Low-Rank Embedded Semantic Dictionary. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018. [pdf][bib][code]
[J-7] Zhengming Ding, and Yun Fu. Dual Low-Rank Decompositions for Robust Cross-View Learning, IEEE Transactions on Image Processing (TIP), vol. 28, no. 1, pp. 194-204, 2019.[pdf][bib][code]
[J-6] Zhengming Ding, Nasser Nasrabadi, and Yun Fu. Semi-supervised Deep Domain Adaptation via Coupled Neural Networks, IEEE Transactions on Image Processing (TIP), vol. 27, no. 11, pp. 5214-5224, Nov. 2018. [pdf][bib][code]
[J-5] Zhengming Ding, and Yun Fu. Deep Domain Generalization with Structured Low-Rank Constraint, IEEE Transactions on Image Processing (TIP), vol. 27, no. 1, pp. 304-313, 2018. [pdf][bib][code]
[J-4] Zhengming Ding, and Yun Fu. Robust Multi-view Data Analysis through Collective Low-Rank Subspace. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 5, pp. 1986-1997, 2018. [pdf][bib][code]
[J-3] Zhengming Ding, Ming Shao, and Yun Fu. Incomplete Multisource Transfer Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 2, pp. 310-323, 2018. [pdf][bib][code]
[J-2] Zhengming Ding, and Yun Fu. Robust Transfer Metric Learning for Image Classification. IEEE Transactions on Image Processing (TIP), vol. 26, no.2, pp. 660-670, 2017. [pdf][bib][code]
[J-1] Zhengming Ding, Ming Shao, and Yun Fu. Missing Modality Transfer Learning via Latent Low-Rank Constraint. IEEE Transactions on Image Processing (TIP), vol. 24, no. 11, pp. 4322-4334, 2015. [pdf][bib][code]

[Full Conference Publications] (3 CVPR, 2 ECCV, 1 ICCV, 9 AAAI, 5 IJCAI, 6 ACM MM, 4 ICDM, etc)

[C-11] Zhengming Ding, and Hongfu Liu. Marginalized Latent Semantic Encoder for Zero-Shot Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [pdf][bib][code]
[C-10] Zhengming Ding, Sheng Li, Ming Shao and Yun Fu. Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation. European Conference on Computer Vision (ECCV), 2018 [pdf]bib][code]
[C-9] Zhengming Ding, Ming Shao, and Yun Fu. Robust Multi-view Representation: A Unified Perspective from Multi-view Learning to Domain Adaption. International Joint Conference on Artificial Intelligence (IJCAI), 2018 (Survey Track) [pdf][bib]
[C-8] Zhengming Ding, Yandong Guo, Lei Zhang, Yun Fu. One-Shot Face Recognition via Generative Learning, IEEE Conference on Automatic Face and Gesture Recognition (FG), 2018. [pdf][bib][code]
[C-7] Zhengming Ding, Ming Shao and Yun Fu. Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [pdf][bib][code]
[C-6] Zhengming Ding, Ming Shao and Yun Fu. Deep Robust Encoder through Locality Preserving Low-Rank Dictionary. European Conference on Computer Vision, (ECCV), 2016. [pdf][bib][code]
[C-5] Zhengming Ding, and Yun Fu. Robust Multi-view Subspace Learning through Dual Low-rank Decompositions. Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016. [pdf][bib][code]
[C-4] Zhengming Ding, Ming Shao, and Yun Fu. Deep Low-rank Coding for Transfer Learning. International Joint Conference on Artificial Intelligence (IJCAI), 2015. [pdf][bib][code]
[C-3] Zhengming Ding, Sungjoo Suh, Jae-Joon Han, Changkyu Choi, and Yun Fu. Discriminative Low-Rank Metric Learning for Face Recognition. International Conference on Automatic Face and Gesture Recognition (FG), 2015.[pdf][bib][code]
[C-2] Zhengming Ding, Yun Fu. Low-Rank Common Subspace for Multi-View Learning. IEEE International Conference on Data Mining (ICDM), 2014. [pdf][bib][code]
[C-1] Zhengming Ding, Ming Shao and Yun Fu. Latent Low-Rank Transfer Subspace Learning for Missing Modality Recognition. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014. [pdf][bib][code]