Email: A@B, A=kaizhu.huang, B=dukekunshan.edu.cn
====
Education Background:====
· Ph.D., Computer Science & Engineering, The Chinese University of Hong Kong (CUHK);
· M.S., Pattern Recognition & Intelligent Systems, Institute of Automation, Chinese Academy of Science (CAS);
· B.Eng., Automation, Xi'an Jiaotong University (XJTU);
Experiences:
· Professor, Data Science Research Center, Duke Kunshan University (2022 - );
· Director, Data Science Research Center, Duke Kunshan University (2023 - );
· Visiting Professor, Department of Intelligent Science, Xi'an Jiaotong-Liverpool University (2022 - );
· Professor, Department of Intelligent Science, Xi'an Jiaotong-Liverpool University (2017 - 2021);
· Associate Dean of Research, School of Advanced Technology (智能工程学院), Xi'an Jiaotong-Liverpool University (2020 -2021 );
· Head, Department of Electrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University, (2016 -2019);
· Founding Director, Suzhou Municipal Key Lab of Cognitive Computing and Applied Technology (2016 - 2021);
· Visiting/Honorary Professor, University of Stirling, UK (2016 - 2018)
· Concurrent Full Professor, University of Electronic Science and Technology of China (2015 - 2017);
· Associate Professor, Department of Electrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University (2013 - 2016);
· Associate Professor, National Laboratory of Pattern Recognition,Chinese Academy of Sciences (2009 - 2012);
· Researcher, Bristol University (2008 - 2009);
· Research Fellow, The Chinese University of Hong Kong (2007 - 2008);
· Research Scientist, Fujitsu R&D Center (2004 - 2007).
Awards & Honours
· 2022: Best Paper Award & Best Oral Presentation Award, International Conference on Machine Vision and Information Technology (CMVIT 2022)
· 2021: Best Paper Runnerup Award & Best Oral Presentation Award, International Conference on Machine Vision and Information Technology (CMVIT 2021)
· 2020: Best Paper Runnerup Award, International Conference on Neural Information Processing (ICONIP 2020)
· 2019: Best Paper Award, 2019 International Conference on Brain Inspired Cognitive Systems (BICS 2019)
· 2019: Best Student Paper Award, 2019 International Conference on Brain Inspired Cognitive Systems (BICS 2019)
· 2018: Best Student Paper Award, 2018 International Conference on Brain Inspired Cognitive Systems (BICS 2018)
· 2017: Best Paper Runner-up Award, 2017 International Conference on Neural Information Processing (ICONIP 2017)
· 2014: Highly Demanded Talent Award of Universities in Suzhou, Suzhou
· 2011: APNNA Young Researcher Award, Asia Pacific Neural Network Society
· 2008: Best Book Award in "三个一百"
· 2007: Postdoctoral Fellowship, Chinese University of Hong Kong
· 2006: Q-finity Award, Fujitsu Laboratories
· 2006: President Award, Fujitsu Laboratories
· 2005: Excellent Research Award, Fujitsu R&D Centre
· 2004: Special Research Award, Fujitsu R&D Centre
· 2001: Postgraduate Scholarship, Chinese University of Hong Kong
Professional Service Activities
Board Member/Advisory Board/Editor· 2012~: Advisory Board in Springer Series in Bio-Neuroinformatics
· 2015~: Section Editor (Senior Associate Editor) in Springer Journal: BMC Big Data Analytics
· 2015~: Senior Co-Section Editor in Cognitive Computation
· 2016~: Associate Editor in Neurocomputing
· 2016~: Advisory Board in Springer Book Series in Cognitive Computation Trend
. 2019~: Action Editor in Neural Networks
. 2021~: Associate Editor in Pattern Recognition
. 2021~: Senior Editor in Journal of Applied Computing and Intelligence
Recent Conference Chairs/PC (Part List)· 2022: International Conference on Machine Vision and Information Technology (General co-Chair)
· 2022: International Conference on Biomedical Signal and Image Processing (General co-Chair)
· 2022: International Conference on Neural Information Processing (Special Session and Workshop co-Chair)
· 2021: Neural Information Processing Systems (NeurIPS 21) (PC)
· 2021: International Conference on Machine Learning (ICML 21) (PC)
· 2021: International Conference on Machine Vision and Information Technology (General co-Chair)
· 2021: International Conference on Joint Artificial Intelligence (IJCAI21) (Senior PC)
· 2021: International Conference on Learning Representation (ICLR 21) (PC)
· 2021: AAAI Conference on Artificial Intelligence (AAAI 21) (PC)
· 2020: International Conference on Neural Information Processing (ICONIP 20) (Workshop co-Chair)
· 2020: World Congress on Computational Intelligence (WCCI 20) (Conflict co-Chair)
· 2020: AAAI Conference on Artificial Intelligence (AAAI 20) (PC)
· 2020: International Conference on Joint Artificial Intelligence (IJCAI20) (PC)
· 2020: European Conference on Computer Vision (ECCV20) (PC)
· 2020: International Conference on Learning Representation (ICLR 20) (PC)
· 2020: Neural Information Processing Systems (NeurIPS 20) (PC)
· 2019: International Conference on Bio-Inspired Computing Systems (BICS 2019) (Program co-Chair)
· 2019: IJCAI19-International Workshop on Artificial Intelligence for Business Security (Program co-Chair)
· 2019: ICDM19-International Workshop on Understanding and Harnessing Adversarial Examples (General co-Chair)
· 2019: AAAI Conference on Artificial Intelligence (AAAI 19) (Senior PC)
· 2019: Neural Information Processing Systems (NeurIPS 19) (PC)
· 2019: International Conference on Learning Representation (ICLR19) (PC)
· 2019: International Conference on Joint Artificial Intelligence (IJCAI19) (PC)
· 2019: International Conference on Machine Learning (ICML 2019) (PC)
· 2019: International Joint Conference on Neural Networks (IJCNN 2019) (PC)
· 2018: International Workshop on Artificial Intelligence and Cybersecurity (AIC 2018) (Organizing co-Chair)
· 2018: AAAI Conference on Artificial Intelligence (AAAI 18) (Senior PC)
· 2018: International Joint Conference on Artificial Intelligence (IJCAI 18) (PC)
· 2018: Neural Information Processing Systems (NeurIPS 18) (PC)
· 2018: Artificial Intelligence x Cybernetic Summit (AICS) (Program co-chair)
· 2017: AAAI Conference on Artificial Intelligence (AAAI 17) (Senior PC)
· 2017: International Joint Conference on Artificial Intelligence (IJCAI 17) (PC)
· 2017: International Conference on Neural Information Processing (ICONIP 2017) (Tutorial and Workshop co-Chair)
· 2017: 1st Artificial Intelligence x Cybernetic Summit (AICS) (General co-chair)
· 2017: International Workshop on Artificial Intelligence and Cybersecurity (AIC 2017) (Lead Organizing Chair)
. 2017: International Conference on Smart Grid Technology and Data Processing (Steering Committee Chair)
· 2016: International Workshop on Data Mining and Cybersecurity (AIC 2016) (Organizing Chair)
· 2016: AAAI Conference on Artificial Intelligence (AAAI 16) (Senior PC)
· 2015: Asian Conference on Machine Learning (ACML 2015) (Publication Chair)
· 2015: International Workshop on Scalable Data Analytics (SDA 2015) (Organizing Chair)
· 2014: International Conference on Neural Information Processing (ICONIP 2014) (Program co-Chair)
· 2014: International Workshop on Artificial Intelligence and Cybersecurity (AIC 2014) (Leading Organizing Chair)
· 2013: International Workshop on Artificial Intelligence and Cybersecurity (AIC 2013) (Organizing co-Chair)
· 2012: International Workshop on Artificial Intelligence and Cybersecurity (AIC 2012) (Organizing co-Chair)
· 2011: International Conference on Document Analysis and Recognition (ICDAR 2011) (Publication Chair)
· 2011: First Asian Conference on Patter Recognition (ACPR 2011) (Publicity Chair)
External Grant Reviewer· 2017~: Singapore AI Programme Funding,
· 2012~: Hong Kong RGC Funding,
· 2010~: NSFC,
Member: Committee/Task Force· 2012-~: CCF National Committee member of Artificial Intelligence and Pattern Recognition,
· 2014-~: National Artificial Intelligence Society: Committee member of Pattern Recognition
Selected Journal Publications (from 100+)
Publication by DBLP Publication by Google Scholar Detailed Publication. Jiezhu Chen, Kaizhu Huang, Zibing Zheng, Fitting Imbalanced Uncertainties in Multi-Output Time Series Forecasting，
ACM Transactions on Knowledge Discovery from Data , 2023.
. Chenru Jiang, Kaizhu Huang, Shufei Zhang, Xinheng Wang, Jimin Xiao， Aggregated Pyramid Gating Network for Human Pose Estimation without Pre-training，
Pattern Recognition, 2023.
. Jingwei Guo, Kaizhu Huang, Xinping Yi, Rui Zhang, Learning Disentangled Graph Convolutional Networks Locally and Globally,
IEEE Transactions on Neural Networks and Learning Systems, 2022.
. Penglei Gao, Xi Yang, Kaizhu Huang, Rui Zhang, Yannis Goulermas, Explainable Tensorized Neural Ordinary Differential Equations for Arbitrary-step Time Series Prediction,
IEEE Transactions on Knowledge and Data Engineering, accepted, 2022.
. Chenru Jiang, Kaizhu Huang, Shufei Zhang, Xinheng Wang, Jimin Xiao, Zhenxin Niu, Amir Hussain,Towards Simple and Accurate Human Pose Estimation with Stair Network,
IEEE Transactions on Emerging Topics in Computational Intelligence, 2022
. Yangfan Zhou, Kaizhu Huang, Cheng, Cheng; Wang, Xuguang; Hussain, Amir; Liu, Xin, FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity ,
IEEE Transactions on Neural Networks and Learning Systems, 2022.
. Yangfan Zhou, Kaizhu Huang, Cheng, Cheng; Wang, Xuguang; Hussain, Amir; Liu, Xin,Towards Faster Training Algorithms Exploiting Bandit Sampling from Convex to Strongly Convex Conditions,
IEEE Transactions on Emerging Topics in Computational Intelligence, 2022
. Zihan Ye, Fuyuan Hu, Fan Lyu, Linyan Li, Kaizhu Huang, Disentangling Semantic-to-visual Confusion for Zero-shot Learning,
IEEE Transactions on Multimedia 2022.
. Kai Yao, Zixian Su, Kaizhu Huang, Xi Yang, Jie Sun, Amir Hussain, A novel 3D unsupervised domain adaptation framework for cross-modality medical image segmentation,
IEEE Journal of Biomedical and Health Informatics, 2022.
. Haotian Xu, Xiaobo Jin, Qiufeng Wang, Amir Hussain, Kaizhu Huang, Exploiting Attention-Consistency Loss For Spatial-Temporal Stream Action Recognition,
ACM Transactions on Multimedia Computing Communications and Applications, accepted, 2022.
. Xiao-Bo Jin, Jianyu Miao, Qiufeng Wang, Guanggang Geng, Kaizhu Huang, Sparse Matrix Factorization with L21 Norm for Matrix Completion,
Pattern Recognition, 2022.
. Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Kaizhu Huang,Shan Luo, Yao Zhao, End-to-End Weakly Supervised Semantic Segmentation with Reliable Region Mining,
Pattern Recognition, 2022.
. Chenru Jiang, Kaizhu Huang, Junwei Wu, Xinheng Wang, Jimin Xiao, Amir Hussain, PointGS: Bridging and Fusing Geometric and Semantic Space for 3D Point Cloud Analysis,
Information Fusion, 2022.
. Shufei Zhang, Kaizhu Huang, Zenglin Xu, Re-thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples,
Machine Learning, 2022
. Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang, Xu-Yao Zhang, A Survey of . Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies,
Pattern Recognition, 2022.
. Qi Chen, Wei Wang, Kaizhu Huang, Frans Coenen, Zero-shot Text Classification via Knowledge Graph Embedding for Social Media Data,
IEEE Internet of Things Journal, accepted, 2021.
. Dong, Hang; Wang, Wei; Huang, Kaizhu; Coenen, Frans Automated Social Text Annotation with Joint Multi-Label Attention Networks,
IEEE Transactions on Neural Networks and Learning Systems, 32(5), 2224-2238, 2021.
. Shufei Zhang, Kaizhu Huang, Jianke Zhu, Yang Liu, Manifold Adversarial Training for Supervised and Semi-supervised Learning,
Neural Networks, accepted, 2020.
. Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Jimin Xiao, Rui Zhang, Generative Adversarial Classifier for Handwriting Characters Super-Resolution,
Pattern Recognition, 107: 107453, 2020. (JCR Q1)
. Kaizhu Huang, Shufei Zhang, Rui Zhang, Amir Hussain, Pattern Field Classification Using Deep Neural Networks,
Neural Networks, 127: 82-95, 2020.
. Fangzhou Xiong, Zhiyong Liu, Kaizhu Huang, Xu Yang, and Amir Hussain, Encoding Primitives Generation Policy Learning for Robotic Arm to Overcome Catastrophic Forgetting in Sequential Multi-tasks Learning,
Neural Networks, 129: 163-173,2020. (JCR Q1)
. Hang Dong, Wei Wang, Kaizhu Huang, Frans Coenen, Knowledge Base Enrichment by Relation Learning from Social Tagging Data,
Information Sciences, 526: 203-220, 2020. (JCR Q1)
. Guoqiang Zhong, Yang Chen, Kaizhu Huang, Generative Adversarial Networks with Decoder-Encoder Output Noises,
Neural Networks,127: 19-28, 2020.
. Yanchun Xie, Jimin Xiao, Kaizhu Huang, Jeyarajan Thiyagalingam, Yao Zhao, Correlation Filter Selection for Visual Tracking Using Reinforcement Learning,
IEEE Transactions on Circuits and Systems for Video Technology, 30(1): 192-204, 2020.
. Jinxuan Sun, Guoqiang Zhong, Yang Chen, Yongbin Liu, Tao Li, Kaizhu Huang: Generative adversarial networks with mixture of t-distributions noise for diverse image generation.
Neural Networks,122: 374-381, 2020
. Xiaobo Jin, Xu-Yao Zhang,
Kaizhu Huang, Guanggang Geng, Stochastic Conjugate Gradient Algorithm with Variance Reduction,
IEEE Transactions on Neural Networks and Learning Systems, 30(5): 1360-1369, 2019.
. Fanzhou Xiong, Biao Sun, Xu Yang,
Kaizhu Huang, Hong Qiao, Amir Hussain, Zhi-Yong Liu,Guided Policy Search for Sequential Multi-Task Learning,
IEEE Transactions on Systems Man and Cybernetics-Systems, 49(1): 216-226, 2019.
. Jimin Xiao, Yanchun Xie, Tammam Tillo,
Kaizhu Huang, Yunchao Wei, Jiashi Feng:
IAN: The Individual Aggregation Network for Person Search.
Pattern Recognition . 87: 332-340 (2019)
. Jieming Ma, Haochuan Jiang, Ziqiang Bi,
Kaizhu Huang et al. , Maximum Power Point Estimation for Photovoltaic Strings Subjected to Partial Shading Scenarios,
IEEE Transactions on Industry Applications, 1890 - 1902, Volume: 55 , Issue: 2, 2019.
. Xi Yang,
Kaizhu Huang, Rui Zhang, Amir Hussain, Learning Latent Features with Infinite Non-negative Binary Matrix Tri-factorization,
IEEE Transactions on Emerging Topics in Computational Intelligence, 2(6): 450-463, 2018.
. Changzhi Luo, Meng Wang,
Kaizhu Huang, Jiashi Feng, Zero-Shot Learning via Attribute Regression and Class Prototype Rectification,
IEEE Transactions on Image Processing, 27(2):637-648, 2018. (JCR Q1)
. Xiao-Bo Jin, Guang-Gang Geng, Guo-Sen Xie,
Kaizhu Huang, Pair-wise Loss for Optimizing NDCG Approximately,
Information Sciences, Volume 453, Pages 50-65, 2018. (JCR Q1)
. Jianyu Sun, Guoqiang Zhong, Kaizhu Huang, Junyu Dong, Banzhaf Random Forests: Cooperative Game Theory Based Random Forests with Consistency,
Neural Networks , 106: 20-29, 2018. (JCR Q1)
.
Kaizhu Huang, Haochuan Jiang, Xu-Yao Zhang, Rui Zhang, Field Support Vector Machines,
IEEE Transactions on Emerging Topics in Computational Intelligence, 1(6), 454-463, 2017.
. Jieming Ma, Haochuan Jiang,
Kaizhu Huang, Ziqiang Bi, Kalok Man, Novel Field-Support Vector Regression-Based Soft Sensor for Accurate Estimation of Solar Irradiance,
IEEE Transactions on Circuits and Systems I, 64(12): 3183-3191, 2017.
. Yao Lu,
Kaizhu Huang, Cheng-Lin Liu, A fast projected fixed-point algorithm for large graph matching,
Pattern Recognition, 60: 971-982, 2016 .
· Haiqin Yang,
Kaizhu Huang, Irwin King, Michael R. Lyu, Maximum Margin Semi-supervised Learning with Irrelevant Data,
Neural Networks, 70: 90-102, 2015.
· Yan-Ming Zhang,
Kaizhu Huang, Cheng-Lin Liu, MTC: A Fast and Robust Graph-based Transductive Learning Algorithm,
IEEE Transactions on Learning Systems and Neural Networks, 26(9): 1979-1991, 2015. (2014 ISI Impact Factor 4.370)
· Xu-Yao Zhang, Peipei Yang, Yan-Ming Zhang,
Kaizhu Huang, and Cheng-Lin Liu, Combination of Classification and Clustering Results with Label Propagation,
IEEE Signal Processing Letters, 21(5): 610-614, 2014. (2012 ISI Impact Factor 1.674)
· Yan-Ming Zhang,
Kaizhu Huang, Xinwen Hou, and Cheng-Lin Liu, Learning Locality Preserving Graph from Data,
IEEE Trans. Cybnetics, 44(11): 2088-2098, 2014.
· Xu-Cheng Yin, Kuang Yin,
Kaizhu Huang, Hong-Wei Hao, Robust Text Detection in Natural Images,
IEEE Trans. on Pattern Analysis and Machine Intelligence, 36(5): 970-983, 2014.
· Xu-Cheng Yin,
Kaizhu Huang, Hong-Wei Hao, Convex Ensemble Learning with Sparsity and Diversity,
Information Fusion, 2014.
· Peipei Yang,
Kaizhu Huang, Cheng-lin Liu, Geometry Preserving Multi-task Metric Learning,
Machine Learning, Volume 92(1), 133-175, 2013.
· Bo Xu,
Kaizhu Huang, Cheng-Lin Liu: Maxi-Min Discriminant Analysis via Online Learning.
Neural Networks 34: 56-64, 2012.
·
Kaizhu Huang, Danian Zheng, Irwin King, Michael R. Lyu, Arbitrary Norm Support Vector Machines.
Neural Computation, Vol. 21, No. 2: 560–582, 2009.
· Zenglin Xu,
Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu: A novel kernel-based maximum a posteriori classification method.
Neural Networks 22(7): 977-987, 2009.
·
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu. M4: Learning Large Margin Machines Locally and Globally,
IEEE Trans. Neural Networks, vol. 19, iss. 2, pp. 260-272, 2008.
·
Kaizhu Huang, Haiqin Yang, Irwin King, and Michael R. Lyu, Maximizing Sensitivity in Medical Diagnosis Using Biased Minimax Probability Machine.
IEEE Trans. Biomedical Engineering, Vol 53, Issue 5, 821- 831, May 2006.
·
Kaizhu Huang, Haiqin Yang, Irwin King, and Michael R. Lyu, Imbalanced Learning With Biased Minimax Probability Machine.
IEEE Trans. System Man, Cybnetics, Part B, Vol 36, No 4, 913 – 923, August, 2006.
·
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, and Laiwan Chan, The Minimum Error Minimax Probability Machine.
Journal of Machine Learning Research, Vol. 5, pp. 1253-1286, October 2004.
Selected Conference Publications (from 110+)
. Jingwei Guo, Kaizhu Huang, Xinping Yi, Rui Zhang, Graph Neural Networks with Diverse Spectral Filtering, ACM Web Conference (
WWW), 2023.
. Zixian Su, Kai Yao, Xi Yang, Qiufeng Wang, Jie Sun,Kaizhu Huang， Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation， (
AAAI), 2023.
. Kai Yao, Penglei Gao,
Kaizhu Huang, Xi Yang, Jie Sun, Rui Zhang, Outpainting by Queries, European Conference on Computer Vision (
ECCV), 2022.
. Zhiqiang Gao, Shufei Zhang,
Kaizhu Huang, Qiufeng Wang, Rui Zhang, Chaoliang Zhong, Certifying Better Robust Generalization for Unsupervised Domain Adaptation, ACM Multimedia (
ACM MM), 2022.
. Global-aware Beam Search for Neural Abstractive Summarization, Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang, Neural Information Processing Systems (
NeurIPS), 2021.
. Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing, Liuqing Zhao, Fan Lyu, Fuyuan Hu, Fenglei Xu, Kaizhu Huang, British Machine Vision Conference (
BMVC), 2021.
. Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation, Zhiqiang Gao, Shufei Zhang, Kaizhu Huang*, Qiufeng Wang, Chaoliang Zhong, International Conference on Computer Vision (
ICCV), 2021.
. Towards Better Robust Generalization with Shift Consistency Regularization, Shufei Zhang, Zhuang Qian,
Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi, International Conference on Machine Learning (
ICML), 2021.
. Pay Attention Selectively and Comprehensively: Pyramid Gating Network for Human Pose Estimation without Pretraining, Chenru Jiang,
Kaizhu Huang, Shufei Zhang, Henry Wang and Jimin Xiao, ACM Multimedia (
ACM MM), 2020.
. Inductive Generalized Zero-shot Learning with Adversarial Relation Network, Guanyu Yang,
Kaizhu Huang, Rui Zhang, John Goulermas and Amir Hussain, European Conference on Machine Learning (
ECML), 2020.
. Matching Representations Matters: End-to-End Learning for Neural Texture Transfer, Yanchun Xie, Jimin XIAO, Mingjie Sun, Chao Yao,
Kaizhu Huang, European Conference on Computer Vision (
ECCV), 2020.
(spotlight paper, acceptance rate 5%).
. Jiezhu Cheng,
Kaizhu Huang, Zibin Zheng, Towards Better Forecasting by Fusing Near and Distant Future Visions, Thirty-Fourth AAAI Conference on Artificial Intelligence (
AAAI), 2020.
. Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Mingjie Sun,
Kaizhu Huang, Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach, Thirty-Fourth AAAI Conference on Artificial Intelligence (
AAAI), 2020.
. Xiao-Bo Jin, Guo-Sen Xie,
Kaizhu Huang, Jianyu Miao, Qiufeng Wang, Beyond Attributes: High-order Attribute Features for Zero-shot Learning, In International Conference on Computer Vision Workshop (
ICCV-W), 2019.
. Shufei Zhang,
Kaizhu Huang, Rui Zhang, and Amir Hussain, Generalized Adversarial Training in Riemannian Space , In
IEEE Fifteen Conference on Data Mining (ICDM’2019) , 2019.
·Xi Yang, Yuyao Yan,
Kaizhu Huang, and Rui Zhang, VSB-DVM: An End-to-end Bayesian Nonparametric Generalization of Deep Variational Mixture Model, In
IEEE Fifteen Conference on Data Mining (ICDM’2019), 2019.
· Hang Dong, Wei Wang,
Kaizhu Huang and Frans Coenen, Joint Multi-Label Attention Networks for Social Text Annotation, In
Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019)" , 2019 .
· Chunchun Lv, Kaizhu Huang
, and Hai-Ning Liang, A Unified Gradient Regularization Family for Adversarial Examples, In
IEEE Fifteen Conference on Data Mining (ICDM’2015) , 2015.
·
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Scalable Data Analytics: Theory and Applications, in
Eighth ACM International Conference on Web Search and Data Mining (WSDM’2015), 2015.
· Xu-Yao Zhang,
Kaizhu Huang, and Chenglin Liu, Feature Transformation with Class Conditional Decorrelation. In
IEEE Thirteen Conference on Data Mining (ICDM’2013), pages 887-896, 2013.
· Yan-Ming Zhang,
Kaizhu Huang, Guanggang Geng, Cheng-Lin Liu, Fast kNN Graph Construction with Locality Sensitive Hashing, In
European conference on Machine Learning (ECML’2013).
· Xu-Cheng Yin, Xuwang Yin,
Kaizhu Huang, Hong-Wei Hao, Accurate and Robust Text Detection: A Step-In for Text Retrieval in Natural Scene Images,
ACM Special Interest Group on Information Retrieval (SIGIR’2013), pages 1091-1092, 2013.
· Peipei Yang,
Kaizhu Huang, and Cheng-Lin Liu, Geometry Preserving Multi-task Metric Learning. In
European conference on Machine Learning (ECML’2012), LNCS Vol.7523, pp.648-664, 2012
· Guoqiang Zhong,
Kaizhu Huang, and Cheng-Lin Liu, Low Rank Metric Learning with Manifold Regularization. In
IEEE Eleventh conference on Data Mining (ICDM’2011), 1266-1271, 2011. '
· Yan-Ming Zhang,
Kaizhu Huang, and Cheng-Lin Liu，Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut,
IEEE Eleventh conference on Data Mining (ICDM’2011), 952-961, 2011.
· Xu-Yao Zhang,
Kaizhu Huang, and Cheng-Lin Liu, Pattern Field Classification with Style Normalized Transformation, In
The International Joint Conference on Artificial Intelligence (IJCAI’2011), 1621-1626, 2011.
·
Kaizhu Huang, Rong Jin, Zenglin Xu, and Cheng-Lin Liu Robust Metric Learning with Smooth Optimization , In T
he 26th Conference on Uncertainty in Artificial Intelligence (UAI’2010), 244-251,2010.
·
Kaizhu Huang, Yiming Ying, Colin Campbell, GSML: A Unified Framework for Sparse Metric Learning，
IEEE Ninth conference on Data Mining (ICDM’2009), 189-198, 2009.
· Yiming Ying,
Kaizhu Huang, Colin Campbell,, Sparse Metric Learning via Smooth Optimization, in
Proc. Advances in Neural Information Processing System 22 (NeurIPS’2009), Cambridge, MA, 2009.
· Zenglin Xu, Rong Jin,
Kaizhu Huang, Irwin King, Michael R. Lyu, Semi-supervised Text Categorization by Active Search, In
ACM 17th Conference on Information and Knowledge Management (CIKM’2008), 1517-1518, 2008.
·
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Semi-supervised Learning from General Unlabeled Data, In
IEEE Eighth conference on Data Mining (ICDM’2008), 273-282, 2008.
·
Kaizhu Huang, Irwin King, Michael R. Lyu, Direct Zero-norm Optimization for Feature Selection, In
IEEE Eighth Conference on Data Mining (ICDM’2008), 845-850, 2008.
·
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine. Proceedings
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’2004), 558-563, Washington, DC, June 27 -July 2, 2004.
·
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Learning Large Margin Machines Locally and Globally.
Proceedings international Conference on Machine Learning (ICML’2004), Banff, Canada, pp. 401-408, 2004.
Professional Memberships
· IEEE
· ACM