Jianbo Yang

Biography

I am currently with Tencent Ads.  Prior to that, I was a a lead machine learning researcher at GE, San Ramon, CA

Before I moved to industry, I was a postdoctoral researcher at Duke University, working with Dr. Lawrence Carin, Dr. Guillermo Sapiro  and Dr. David Brady. In my last year of PhD, I was a research fellow at Nanyang Technological University. I obtained my PhD degree from National University of Singapore and completed M.Eng and  B.Eng degrees at Sichuan University


My research interests lie in machine learning, including the following topics:


Software            


Publication

SCRIPT: Sequential Cross-Meta-Information Recommendation in Pretrain and Prompt Paradigm

Xinyi Zhou, Jipeng Jin, Li Ma, Xiaofeng Gao, Jianbo Yang, Xiongwen Yang, Lei Xiao

Proceedings of the International Conference on Data Mining (ICDM), 2023


Meta Hyperparameter Optimization with Adversarial Proxy Subsets Sampling [PDF]

Yue Liu,  Xin Wang,  Xue Xu,  Jianbo Yang,  Wenwu Zhu

Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM), 2021


Representative Negative Instance Generation for Online Ad Targeting [PDF]

Yuhan Quan, Jingtao Ding, Depeng Jin, Jianbo Yang, Xing Zhou, Yong Li

Proceedings of the 29th ACM International Conference on Information & Knowledge Management (CIKM), 2020


Diabetic Retinopathy Detection via Deep Convolutional Networks for Discriminative Localization and Visual Explanation. [PDF]

Zhiguang Wang, Jianbo Yang

arXiv preprint arxiv: 1703.10757, 2017.


Repeat Buyer Prediction for E-Commerce [PDFThe First Prize of IJCAI 2015 Stage 1 Repeat Buyers Prediction Competition

Guimei Liu, Tam Nguyen, Gang Zhao, Wei Zha, Jianbo Yang, Jianneng Cao, Min Wu,  Peilin Zhao and Wei Chen

International Conference on Knowledge Discovery and Data Mining (KDD), 2016.


Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Noisy Features in the Presence of Side Information [PDF]

F. Renna, L. Wang, X. Yuan, Jianbo Yang, G. Reeves, R. Calderbank, L. Carin, and M.R.D. Rodrigues.

IEEE Transactions on Information Theory (TIT), 2016.


Deep Convolutional Neural Networks on Multichannel Time Series For Human Activity Recognition [PDF][Code(v1.0)]

Jianbo Yang, MinhNhut Nguyen, PhyoPhyo San, Xiaoli Li and Shonali Krishnaswamy 

International Joint Conference on Artificial Intelligence (IJCAI), 2015.


Compressive Sensing of Signals from a GMM with Sparse Precision Matrices [PDF] [Supplementary Material]

Jianbo Yang, Xuejun Liao, Minhua Chen, and Lawrence Carin 

Neural Information Processing Systems (NIPS), 2014.


Compressive Sensing by Learning a Gaussian Mixture Model from Measurements [PDF][Code(v1.1)]

Jianbo Yang Xuejun Liao, Xin Yuan, Patrick Llull, David J. Brady, Guillermo Sapiro and Lawrence Carin 

IEEE Transactions on Image Processing  (TIP)  vol. 24, no. 1, pp. 106-119, 2015.


Coded aperture compressive temporal color imaging [PDF]

Patrick Llull, Xuejun Liao,  Xin Yuan, Jianbo Yang,  David Kittle, Lawrence Carin, Guillermo Sapiro and David J. Brady

an invited book chapter in " Compressed Sensing and Its Applications", Editors, Gitta Kutyniok et al. ,Springer. 2015.


Classification and Reconstruction of Compressed GMM Signals with Side Information [PDF]

F. Renna, L. Wang, X. Yuan, Jianbo Yang, G. Reeves, R. Calderbank, L. Carin and M. R. D. Rodrigues

IEEE International Symposium on Information Theory (ISIT), 2015.


Video Compressive Sensing Using Gaussian Mixture Models [PDF] [Code(v1.1)]

Jianbo Yang, Xin Yuan, Xuejun Liao, Patrick Llull, David J. Brady, Guillermo Sapiro and Lawrence Carin

IEEE Transactions on Image Processing (TIP)  vol. 23, no. 11, pp. 4863-4878, 2014.


Compressive Extended Depth of Field Using Image Space Coding [PDF] Best Paper Award

Patrick Llull, Xin Yuan, Xuejun Liao, Jianbo Yang, Lawrence Carin, Guillermo Sapiro and David J. Brady

Computational Optical Sensing and Imaging (COSI) , 2014.


Low-Cost Compressive Sensing for Color Video and Depth [PDF][Website]

Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady and Lawrence Carin

IEEE Computer Vision and Pattern Recognition (CVPR), 2014.


Adaptive Temporal Compressive Sensing for Video [PDF]

Xin Yuan, Jianbo Yang, Xuejun Liao, Patrick Llull, Guillermo Sapiro, David J. Brady and Lawrence Carin

International Conference on Image Processing (ICIP), 2013.


Gaussian Mixture Model for Video Compressive Sensing [PDF]

Jianbo Yang, Xin Yuan, Xuejun Liao, Patrick Llull, Guillermo Sapiro, David J. Brady and Lawrence Carin

International Conference on Image Processing (ICIP), 2013.


Compressive Sensing for Video Using a Passive Coding Element [PDF] Best Paper Award

Patrick Llull, Xuejun Liao, Xin Yuan, Jianbo Yang, David Kittle, Lawrence Carin, Guillermo Sapiro and David J. Brady

Computational Optical Sensing and Imaging (COSI) 2013.


Coded Aperture Compressive Temporal Imaging [PDF

Patrick Llull, Xuejun Liao, Xin Yuan, Jianbo Yang, David Kittle, Lawrence Carin, Guillermo Sapiro and David J. Brady

Optics Express (OE), vol. 21, no. 9,pp. 10536-10545, 2013.


Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach [PDF]

Jianbo Yang, Qi Mao, Qiao Liang Xiang, Ivor W. Tsang, Kian Ming Adam Chai and Hai Leong Chieu

In Proc. of  the Conference on Empirical Methods in Natural Language Processing and Conference on Natural Language Learning (EMNLP), 2012.


An Effective Feature Selection Method via Mutual Information Estimation [PDF]

Jianbo Yang and Chong-Jin Ong

IEEE Transactions on  Systems, Man and Cybernetics (Part B) (TSMC-B), vol. 42, no. 6, pp. 1550 - 1559, 2012.


Hierarchical Maximum Margin Learning for Multi-Class Classification [PDF]

Jianbo Yang and Ivor W. Tsang

In Proc. of the 27th Conference on Uncertainty in Artificial Intelligence (UAI), Barcelona, Spain, pp. 753-760, 2011. 


Determination of Global Minima of Some Common Validation Functions in Support Vector Machine [PDF]

Jianbo Yang and Chong-Jin Ong

IEEE Transactions on Neural Network (TNN), vol. 22, no. 4, pp. 654 - 659, 2011.


Feature Selection using Probabilistic Prediction of Support Vector Regression [PDF][Code(v1.0)]

Jianbo Yang and Chong-Jin Ong

IEEE Transactions on Neural Network (TNN), vol. 22, no. 6, pp. 954 - 962, 2011.


Feature Selection for Support VectorRegression Using Probabilistic Prediction [PDF][Code(v1.0)]

Jianbo Yang and Chong-Jin Ong

In Proc. of the 16th ACM  International Conference on Knowledge Discovery and Data Mining (KDD) , Washington DC, USA, pp. 343--352, 2010.


An Improved Algorithm for the Solution of theRegularization Path of Support Vector Machine [PDF]

Chong-Jin Ong, Shi-Yun Shao and Jianbo Yang

IEEE Transactions on Neural Network (TNN), vol. 21, no. 3, pp. 451 - 462, 2010.


Feature Selection for MLP Neural Network: TheUse of Random Permutation of Probabilistic Outputs [PDF

Jianbo Yang, Kai-Quan Shen, Chong-Jin Ong, and Xiao-Ping Li

IEEE Transactions on Neural Network (TNN), vol. 20, no. 12, pp. 1911 - 1922, 2009. 


Feature selection via sensitivity analysis ofMLP probabilistic outputs [PDF]

Jianbo Yang, Kai-Quan Shen, Chong-Jin Ong, and Xiao-Ping Li

2008 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 774 - 779, Singapore,2008.



Jianbo Yang,  “Feature selection and model selection for supervised learning algorithms”  PhD Thesis, 2011. 


Professional Activities 

Peer Reviewing


Program Committee Member



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