Scholars@Duke

• Background
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  Education, Training, & Certifications

  • Ph.D., Chinese University of Hong Kong (Hong Kong) 2004
• Publications & Artistic Works
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  Selected Publications

  • Books

    • Gao, H., X. Wang, Y. Yang, K. Huang, and T. Lu. Preface. Vol. 407 LNICST, 2021.
    • Zhong, G., and K. Huang. Semi-supervised learning: Background, applications and future directions, 2018.
    • Zhong, G., and K. Huang. Preface, 2018.
    • Loo, C. K., K. S. Yap, K. W. Wong, A. Teoh, and K. Huang. Preface. Vol. 8835, 2014. https://doi.org/10.1007/978-3-319-12640-1.
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    • Huang, K., H. Yang, I. King, and M. R. Lyu. Preface, 2008.

  • Academic Articles

    • Gao, P., X. Yang, R. Zhang, K. Huang, and J. Y. Goulermas. “Explainable Tensorized Neural Ordinary Differential Equations for Arbitrary-Step Time Series Prediction (Accepted).” Ieee Transactions on Knowledge and Data Engineering 35, no. 6 (June 1, 2023): 5837–50. https://doi.org/10.1109/TKDE.2022.3167536.
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    • Gao, Penglei, Xi Yang, Rui Zhang, John Y. Goulermas, Yujie Geng, Yuyao Yan, and Kaizhu Huang. “Generalized image outpainting with U-transformer.” Neural Networks : The Official Journal of the International Neural Network Society 162 (May 2023): 1–10. https://doi.org/10.1016/j.neunet.2023.02.021.
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    • Zhou, Y., K. Huang, J. Li, C. Cheng, X. Wang, A. Hussian, and X. Liu. “Randomized block-coordinate adaptive algorithms for nonconvex optimization problems.” Engineering Applications of Artificial Intelligence 121 (May 1, 2023). https://doi.org/10.1016/j.engappai.2023.105968.
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    • Sun, J., K. Yao, G. Huang, C. Zhang, M. Leach, K. Huang, and X. Yang. “Machine Learning Methods in Skin Disease Recognition: A Systematic Review.” Processes 11, no. 4 (April 1, 2023). https://doi.org/10.3390/pr11041003.
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    • Zhou, Y., K. Huang, C. Cheng, X. Wang, A. Hussain, and X. Liu. “Towards Faster Training Algorithms Exploiting Bandit Sampling From Convex to Strongly Convex Conditions.” Ieee Transactions on Emerging Topics in Computational Intelligence 7, no. 2 (April 1, 2023): 565–77. https://doi.org/10.1109/TETCI.2022.3171797.
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    • Xu, H., X. Jin, Q. Wang, A. Hussain, and K. Huang. “Exploiting Attention-Consistency Loss For Spatial-Temporal Stream Action Recognition.” Acm Transactions on Multimedia Computing, Communications and Applications 18, no. 2 S (October 6, 2022). https://doi.org/10.1145/3538749.
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    • Yao, Kai, Zixian Su, Kaizhu Huang, Xi Yang, Jie Sun, Amir Hussain, and Frans Coenen. “A Novel 3D Unsupervised Domain Adaptation Framework for Cross-Modality Medical Image Segmentation.” Ieee Journal of Biomedical and Health Informatics 26, no. 10 (October 2022): 4976–86. https://doi.org/10.1109/jbhi.2022.3162118.
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    • Guo, Jingwei, Kaizhu Huang, Xinping Yi, and Rui Zhang. “Learning Disentangled Graph Convolutional Networks Locally and Globally.” Ieee Transactions on Neural Networks and Learning Systems PP (August 2022). https://doi.org/10.1109/tnnls.2022.3195336.
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    • Chen, Q., W. Wang, K. Huang, and F. Coenen. “Zero-Shot Text Classification via Knowledge Graph Embedding for Social Media Data.” Ieee Internet of Things Journal 9, no. 12 (June 15, 2022): 9205–13. https://doi.org/10.1109/JIOT.2021.3093065.
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    • Zhou, Y., K. Huang, C. Cheng, X. Wang, and X. Liu. “LightAdam: Towards a Fast and Accurate Adaptive Momentum Online Algorithm.” Cognitive Computation 14, no. 2 (March 1, 2022): 764–79. https://doi.org/10.1007/s12559-021-09985-9.
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    • Jiang, C., K. Huang, S. Zhang, X. Wang, J. Xiao, Z. Niu, and A. Hussain. “Towards Simple and Accurate Human Pose Estimation With Stair Network.” Ieee Transactions on Emerging Topics in Computational Intelligence, January 1, 2022. https://doi.org/10.1109/TETCI.2022.3224954.
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    • Yao, Kai, Jie Sun, Kaizhu Huang, Linzhi Jing, Hang Liu, Dejian Huang, and Curran Jude. “Analyzing Cell-Scaffold Interaction through Unsupervised 3D Nuclei Segmentation.” International Journal of Bioprinting 8, no. 1 (January 2022): 495. https://doi.org/10.18063/ijb.v8i1.495.
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    • Ye, Z., F. Hu, F. Lyu, L. Li, and K. Huang. “Disentangling Semantic-to-Visual Confusion for Zero-Shot Learning.” Ieee Transactions on Multimedia 24 (January 1, 2022): 2828–40. https://doi.org/10.1109/TMM.2021.3089017.
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    • Wang, X., H. Gao, and K. Huang. “Artificial Intelligence in Collaborative Computing.” Mobile Networks and Applications 26, no. 6 (December 1, 2021): 2389–91. https://doi.org/10.1007/s11036-021-01829-y.
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    • Yang, G., K. Huang, R. Zhang, J. Y. Goulermas, and A. Hussain. “Coarse-grained generalized zero-shot learning with efficient self-focus mechanism.” Neurocomputing 463 (November 6, 2021): 400–410. https://doi.org/10.1016/j.neucom.2021.08.027.
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    • Yao, K., K. Huang, J. Sun, L. Jing, D. Huang, and C. Jude. “Scaffold-A549: A Benchmark 3D Fluorescence Image Dataset for Unsupervised Nuclei Segmentation.” Cognitive Computation 13, no. 6 (November 1, 2021): 1603–8. https://doi.org/10.1007/s12559-021-09944-4.
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    • Zhang, S., K. Huang, Z. Qian, R. Zhang, and A. Hussain. “Improving generative adversarial networks with simple latent distributions.” Neural Computing and Applications 33, no. 20 (October 1, 2021): 13193–203. https://doi.org/10.1007/s00521-021-05946-3.
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    • Chen, Q., W. Wang, K. Huang, S. De, and F. Coenen. “Multi-modal generative adversarial networks for traffic event detection in smart cities.” Expert Systems With Applications 177 (September 1, 2021). https://doi.org/10.1016/j.eswa.2021.114939.
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    • Zhang, Shufei, Kaizhu Huang, Jianke Zhu, and Yang Liu. “Manifold adversarial training for supervised and semi-supervised learning.” Neural Networks : The Official Journal of the International Neural Network Society 140 (August 2021): 282–93. https://doi.org/10.1016/j.neunet.2021.03.031.
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    • Jiang, H., K. Huang, R. Zhang, and A. Hussain. “Style-Neutralized Pattern Classification Based on Adversarially Trained Upgraded U-Net.” Cognitive Computation 13, no. 4 (July 1, 2021): 845–58. https://doi.org/10.1007/s12559-019-09660-0.
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    • Zhao, P., W. Zang, B. Liu, Z. Kang, K. Bai, K. Huang, and Z. Xu. “Domain adaptation with feature and label adversarial networks.” Neurocomputing 439 (June 7, 2021): 294–301. https://doi.org/10.1016/j.neucom.2021.01.062.
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    • Dong, Hang, Wei Wang, Kaizhu Huang, and Frans Coenen. “Automated Social Text Annotation With Joint Multilabel Attention Networks.” Ieee Transactions on Neural Networks and Learning Systems 32, no. 5 (May 2021): 2224–38. https://doi.org/10.1109/tnnls.2020.3002798.
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    • Lin, X., G. Zhong, K. Chen, Q. Li, and K. Huang. “Attention-Augmented Machine Memory.” Cognitive Computation 13, no. 3 (May 1, 2021): 751–60. https://doi.org/10.1007/s12559-021-09854-5.
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    • Kanwal, S., A. Hussain, and K. Huang. “Novel Artificial Immune Networks-based optimization of shallow machine learning (ML) classifiers.” Expert Systems With Applications 165 (March 1, 2021). https://doi.org/10.1016/j.eswa.2020.113834.
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    • Xiong, F., Z. Liu, K. Huang, X. Yang, and H. Qiao. “State Primitive Learning to Overcome Catastrophic Forgetting in Robotics.” Cognitive Computation 13, no. 2 (March 1, 2021): 394–402. https://doi.org/10.1007/s12559-020-09784-8.
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    • Qu, Shuyi, Kaizhu Huang, Amir Hussain, and Yannis Goulermas. “A Multipath Fusion Strategy Based Single Shot Detector.” Sensors (Basel, Switzerland) 21, no. 4 (February 2021): 1360. https://doi.org/10.3390/s21041360.
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    • Ma, M., Q. F. Wang, S. Huang, Y. Goulermas, and K. Huang. “Residual attention-based multi-scale script identification in scene text images.” Neurocomputing 421 (January 15, 2021): 222–33. https://doi.org/10.1016/j.neucom.2020.09.015.
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    • Gul, H., A. Amin, A. Adnan, and K. Huang. “A Systematic Analysis of Link Prediction in Complex Network.” Ieee Access, January 1, 2021. https://doi.org/10.1109/ACCESS.2021.3053995.
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    • Ma, Y., G. Zhong, W. Liu, J. Sun, and K. Huang. “Neural CAPTCHA networks.” Applied Soft Computing Journal 97 (December 1, 2020). https://doi.org/10.1016/j.asoc.2020.106769.
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    • Qian, Z., K. Huang, Q. F. Wang, J. Xiao, and R. Zhang. “Generative adversarial classifier for handwriting characters super-resolution.” Pattern Recognition 107 (November 1, 2020). https://doi.org/10.1016/j.patcog.2020.107453.
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    • Wang, Li-Na, Wenxue Liu, Xiang Liu, Guoqiang Zhong, Partha Pratim Roy, Junyu Dong, and Kaizhu Huang. “Compressing Deep Networks by Neuron Agglomerative Clustering.” Sensors (Basel, Switzerland) 20, no. 21 (October 2020): E6033. https://doi.org/10.3390/s20216033.
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    • Wang, Q. F., K. Yao, R. Zhang, A. Hussain, and K. Huang. “Improving deep neural network performance by integrating kernelized Min-Max objective.” Neurocomputing 408 (September 30, 2020): 82–90. https://doi.org/10.1016/j.neucom.2019.08.101.
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    • Xiong, Fangzhou, Zhiyong Liu, Kaizhu Huang, Xu Yang, Hong Qiao, and Amir Hussain. “Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learning.” Neural Networks : The Official Journal of the International Neural Network Society 129 (September 2020): 163–73. https://doi.org/10.1016/j.neunet.2020.06.003.
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    • Wang, X., M. Iqbal, H. Gao, K. Huang, and A. Tchernykh. “Editorial: Collaborative Computing for Data-Driven Systems.” Mobile Networks and Applications 25, no. 4 (August 1, 2020): 1348–50. https://doi.org/10.1007/s11036-019-01452-y.
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    • Zheng, D., J. Xiao, K. Huang, and Y. Zhao. “Segmentation mask guided end-to-end person search.” Signal Processing: Image Communication 86 (August 1, 2020). https://doi.org/10.1016/j.image.2020.115876.
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    • Fang, Z., J. Ren, S. Marshall, H. Zhao, Z. Wang, K. Huang, and B. Xiao. “Triple loss for hard face detection.” Neurocomputing 398 (July 20, 2020): 20–30. https://doi.org/10.1016/j.neucom.2020.02.060.
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    • Dong, H., W. Wang, F. Coenen, and K. Huang. “Knowledge base enrichment by relation learning from social tagging data.” Information Sciences 526 (July 1, 2020): 203–20. https://doi.org/10.1016/j.ins.2020.04.002.
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    • Huang, Kaizhu, Shufei Zhang, Rui Zhang, and Amir Hussain. “Novel deep neural network based pattern field classification architectures.” Neural Networks : The Official Journal of the International Neural Network Society 127 (July 2020): 82–95. https://doi.org/10.1016/j.neunet.2020.03.011.
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    • Zhong, Guoqiang, Wei Gao, Yongbin Liu, Youzhao Yang, Da-Han Wang, and Kaizhu Huang. “Generative adversarial networks with decoder-encoder output noises.” Neural Networks : The Official Journal of the International Neural Network Society 127 (July 2020): 19–28. https://doi.org/10.1016/j.neunet.2020.04.005.
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    • Tesema, F. B., H. Wu, M. Chen, J. Lin, W. Zhu, and K. Huang. “Hybrid channel based pedestrian detection.” Neurocomputing 389 (May 14, 2020): 1–8. https://doi.org/10.1016/j.neucom.2019.12.110.
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    • Sun, Jinxuan, Guoqiang Zhong, Yang Chen, Yongbin Liu, Tao Li, and Kaizhu Huang. “Generative adversarial networks with mixture of t-distributions noise for diverse image generation.” Neural Networks : The Official Journal of the International Neural Network Society 122 (February 2020): 374–81. https://doi.org/10.1016/j.neunet.2019.11.003.
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    • Xie, Y., J. Xiao, K. Huang, J. Thiyagalingam, and Y. Zhao. “Correlation Filter Selection for Visual Tracking Using Reinforcement Learning.” Ieee Transactions on Circuits and Systems for Video Technology 30, no. 1 (January 1, 2020): 192–204. https://doi.org/10.1109/TCSVT.2018.2889488.
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    • Zhong, G., W. Jiao, W. Gao, and K. Huang. “Automatic Design of Deep Networks with Neural Blocks.” Cognitive Computation 12, no. 1 (January 1, 2020): 1–12. https://doi.org/10.1007/s12559-019-09677-5.
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    • Yang, X., K. Huang, R. Zhang, and J. Y. Goulermas. “A Novel Deep Density Model for Unsupervised Learning.” Cognitive Computation 11, no. 6 (December 1, 2019): 778–88. https://doi.org/10.1007/s12559-018-9566-9.
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    • Gao, Z., D. Liu, K. Huang, and Y. Huang. “Context-aware human activity and smartphone position-mining with motion sensors.” Remote Sensing 11, no. 21 (November 1, 2019). https://doi.org/10.3390/rs11212531.
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    • Zhang, L., Z. Liu, S. Zhang, X. Yang, H. Qiao, K. Huang, and A. Hussain. “Cross-modality interactive attention network for multispectral pedestrian detection.” Information Fusion 50 (October 1, 2019): 20–29. https://doi.org/10.1016/j.inffus.2018.09.015.
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    • Jin, X. B., G. S. Xie, K. Huang, H. Cao, and Q. F. Wang. “Discriminant Zero-Shot Learning with Center Loss.” Cognitive Computation 11, no. 4 (August 15, 2019): 503–12. https://doi.org/10.1007/s12559-019-09629-z.
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    • Jin, Xiao-Bo, Xu-Yao Zhang, Kaizhu Huang, and Guang-Gang Geng. “Stochastic Conjugate Gradient Algorithm With Variance Reduction.” Ieee Transactions on Neural Networks and Learning Systems 30, no. 5 (May 2019): 1360–69. https://doi.org/10.1109/tnnls.2018.2868835.
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    • Liu, Z. Y., K. Z. Huang, X. Yang, and C. L. Liu. “Special issue on advances in graph algorithm and applications.” Neurocomputing 336 (April 7, 2019): 1–2. https://doi.org/10.1016/j.neucom.2018.08.083.
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    • Ma, J., H. Jiang, Z. Bi, K. Huang, X. Li, and H. Wen. “Maximum Power Point Estimation for Photovoltaic Strings Subjected to Partial Shading Scenarios.” Ieee Transactions on Industry Applications 55, no. 2 (March 1, 2019): 1890–1902. https://doi.org/10.1109/TIA.2018.2882482.
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    • Xiao, J., Y. Xie, T. Tillo, K. Huang, Y. Wei, and J. Feng. “IAN: The Individual Aggregation Network for Person Search.” Pattern Recognition 87 (March 1, 2019): 332–40. https://doi.org/10.1016/j.patcog.2018.10.028.
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    • Xiong, F., B. Sun, X. Yang, H. Qiao, K. Huang, A. Hussain, and Z. Liu. “Guided policy search for sequential multitask learning.” Ieee Transactions on Systems, Man, and Cybernetics: Systems 49, no. 1 (January 1, 2019): 216–26. https://doi.org/10.1109/TSMC.2018.2800040.
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    • Jin, X. B., G. S. Xie, K. Huang, and A. Hussain. “Accelerating Infinite Ensemble of Clustering by Pivot Features.” Cognitive Computation 10, no. 6 (December 1, 2018): 1042–50. https://doi.org/10.1007/s12559-018-9583-8.
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    • Wajid, S. K., A. Hussain, and K. Huang. “Three-Dimensional Local Energy-Based Shape Histogram (3D-LESH): A Novel Feature Extraction Technique.” Expert Systems With Applications 112 (December 1, 2018): 388–400. https://doi.org/10.1016/j.eswa.2017.11.057.
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    • Yang, X., K. Huang, R. Zhang, and A. Hussain. “Learning Latent Features with Infinite Nonnegative Binary Matrix Trifactorization.” Ieee Transactions on Emerging Topics in Computational Intelligence 2, no. 6 (December 1, 2018): 450–63. https://doi.org/10.1109/TETCI.2018.2806934.
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    • Yang, X., K. Huang, R. Zhang, J. Y. Goulermas, and A. Hussain. “A new two-layer mixture of factor analyzers with joint factor loading model for the classification of small dataset problems.” Neurocomputing 312 (October 27, 2018): 352–63. https://doi.org/10.1016/j.neucom.2018.05.085.
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    • Sun, Jianyuan, Guoqiang Zhong, Kaizhu Huang, and Junyu Dong. “Banzhaf random forests: Cooperative game theory based random forests with consistency.” Neural Networks : The Official Journal of the International Neural Network Society 106 (October 2018): 20–29. https://doi.org/10.1016/j.neunet.2018.06.006.
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    • Jin, X. B., G. G. Geng, G. S. Xie, and K. Huang. “Approximately optimizing NDCG using pair-wise loss.” Information Sciences 453 (July 1, 2018): 50–65. https://doi.org/10.1016/j.ins.2018.04.033.
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    • Changzhi Luo, Hai-Ning, Hai-Ning Zhetao Li, Hai-Ning Kaizhu Huang, Hai-Ning Jiashi Feng, and Hai-Ning Meng Wang. “Zero-Shot Learning via Attribute Regression and Class Prototype Rectification.” Ieee Transactions on Image Processing : A Publication of the Ieee Signal Processing Society 27, no. 2 (February 2018): 637–48. https://doi.org/10.1109/tip.2017.2745109.
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    • Huang, K., R. Zhang, X. Jin, and A. Hussain. “Special Issue Editorial: Cognitively-Inspired Computing for Knowledge Discovery.” Cognitive Computation 10, no. 1 (February 1, 2018). https://doi.org/10.1007/s12559-017-9532-y.
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    • Zhang, S., K. Huang, R. Zhang, and A. Hussain. “Learning from Few Samples with Memory Network.” Cognitive Computation 10, no. 1 (February 1, 2018): 15–22. https://doi.org/10.1007/s12559-017-9507-z.
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    • Zhong, G., S. Yan, K. Huang, Y. Cai, and J. Dong. “Reducing and Stretching Deep Convolutional Activation Features for Accurate Image Classification.” Cognitive Computation 10, no. 1 (February 1, 2018): 179–86. https://doi.org/10.1007/s12559-017-9515-z.
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    • Jiang, C., J. Xiao, Y. Xie, T. Tillo, and K. Huang. “Siamese network ensemble for visual tracking.” Neurocomputing 275 (January 31, 2018): 2892–2903. https://doi.org/10.1016/j.neucom.2017.10.043.
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    • Huang, K., H. Jiang, and X. Y. Zhang. “Field Support Vector Machines.” Ieee Transactions on Emerging Topics in Computational Intelligence 1, no. 6 (December 1, 2017): 454–63. https://doi.org/10.1109/TETCI.2017.2751062.
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    • Ma, J., H. Jiang, K. Huang, Z. Bi, and K. L. Man. “Novel Field-Support Vector Regression-Based Soft Sensor for Accurate Estimation of Solar Irradiance.” Ieee Transactions on Circuits and Systems I: Regular Papers 64, no. 12 (December 1, 2017): 3183–91. https://doi.org/10.1109/TCSI.2017.2746091.
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    • Yang, X., K. Huang, J. Y. Goulermas, and R. Zhang. “Joint Learning of Unsupervised Dimensionality Reduction and Gaussian Mixture Model.” Neural Processing Letters 45, no. 3 (June 1, 2017): 791–806. https://doi.org/10.1007/s11063-016-9508-z.
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    • Amin, A., S. Anwar, A. Adnan, M. Nawaz, K. Alawfi, A. Hussain, and K. Huang. “Customer churn prediction in the telecommunication sector using a rough set approach.” Neurocomputing 237 (May 10, 2017): 242–54. https://doi.org/10.1016/j.neucom.2016.12.009.
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    • Lu, Y., K. Huang, and C. L. Liu. “A fast projected fixed-point algorithm for large graph matching.” Pattern Recognition 60 (December 1, 2016): 971–82. https://doi.org/10.1016/j.patcog.2016.07.015.
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    • Ting, T. O., J. Ma, K. S. Kim, and K. Huang. “Multicores and GPU utilization in parallel swarm algorithm for parameter estimation of photovoltaic cell model.” Applied Soft Computing Journal 40 (March 1, 2016): 58–63. https://doi.org/10.1016/j.asoc.2015.10.054.
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    • Yang, Haiqin, Kaizhu Huang, Irwin King, and Michael R. Lyu. “Maximum margin semi-supervised learning with irrelevant data.” Neural Networks : The Official Journal of the International Neural Network Society 70 (October 2015): 90–102. https://doi.org/10.1016/j.neunet.2015.06.004.
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    • Yin, X. C., K. Huang, and H. W. Hao. “DE²: Dynamic ensemble of ensembles for learning nonstationary data.” Neurocomputing 165 (October 1, 2015): 14–22. https://doi.org/10.1016/j.neucom.2014.06.092.
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    • Zhang, Yan-Ming, Kaizhu Huang, Guang-Gang Geng, and Cheng-Lin Liu. “MTC: A Fast and Robust Graph-Based Transductive Learning Method.” Ieee Transactions on Neural Networks and Learning Systems 26, no. 9 (September 2015): 1979–91. https://doi.org/10.1109/tnnls.2014.2363679.
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    • Huang, K., R. Zhang, and X. C. Yin. “Learning Imbalanced Classifiers Locally and Globally with One-Side Probability Machine.” Neural Processing Letters 41, no. 3 (June 1, 2015): 311–23. https://doi.org/10.1007/s11063-014-9370-9.
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    • Zhang, Yan-Ming, Kaizhu Huang, Xinwen Hou, and Cheng-Lin Liu. “Learning locality preserving graph from data.” Ieee Transactions on Cybernetics 44, no. 11 (November 2014): 2088–98. https://doi.org/10.1109/tcyb.2014.2300489.
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    • Yin, X. C., K. Huang, H. W. Hao, K. Iqbal, and Z. B. Wang. “A novel classifier ensemble method with sparsity and diversity.” Neurocomputing 134 (June 25, 2014): 214–21. https://doi.org/10.1016/j.neucom.2013.07.054.
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    • Yin, Xu-Cheng, Xuwang Yin, Kaizhu Huang, and Hong-Wei Hao. “Robust Text Detection in Natural Scene Images.” Ieee Transactions on Pattern Analysis and Machine Intelligence 36, no. 5 (May 2014): 970–83. https://doi.org/10.1109/tpami.2013.182.
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    • Xu, B., K. Huang, I. King, C. L. Liu, J. Sun, and N. Satoshi. “Graphical lasso quadratic discriminant function and its application to character recognition.” Neurocomputing 129 (April 10, 2014): 33–40. https://doi.org/10.1016/j.neucom.2012.08.073.
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    • Yin, X. C., K. Huang, C. Yang, and H. W. Hao. “Convex ensemble learning with sparsity and diversity.” Information Fusion 20, no. 1 (January 1, 2014): 49–59. https://doi.org/10.1016/j.inffus.2013.11.003.
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    • Zhang, X. Y., P. Yang, Y. M. Zhang, K. Huang, and C. L. Liu. “Combination of classification and clustering results with label propagation.” Ieee Signal Processing Letters 21, no. 5 (January 1, 2014): 610–14. https://doi.org/10.1109/LSP.2014.2312005.
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    • Yang, P., K. Huang, and C. L. Liu. “Geometry preserving multi-task metric learning.” Machine Learning 92, no. 1 (July 1, 2013): 133–75. https://doi.org/10.1007/s10994-013-5379-y.
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    • Yang, P., K. Huang, and C. L. Liu. “A multi-task framework for metric learning with common subspace.” Neural Computing and Applications 22, no. 7–8 (June 1, 2013): 1337–47. https://doi.org/10.1007/s00521-012-0956-8.
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    • Xu, Bo, Kaizhu Huang, and Cheng-Lin Liu. “Maxi-Min discriminant analysis via online learning.” Neural Networks : The Official Journal of the International Neural Network Society 34 (October 2012): 56–64. https://doi.org/10.1016/j.neunet.2012.06.001.
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    • Zhong, G., K. Huang, and C. L. Liu. “Joint learning of error-correcting output codes and dichotomizers from data.” Neural Computing and Applications 21, no. 4 (June 1, 2012): 715–24. https://doi.org/10.1007/s00521-011-0653-z.
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    • Wang, Z. B., H. W. Hao, X. C. Yin, Q. Liu, and K. Huang. “Exchange rate prediction with non-numerical information.” Neural Computing and Applications 20, no. 7 (October 1, 2011): 945–54. https://doi.org/10.1007/s00521-010-0393-5.
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    • Yin, X. C., Q. Liu, H. W. Hao, Z. B. Wang, and K. Huang. “FMI image based rock structure classification using classifier combination.” Neural Computing and Applications 20, no. 7 (October 1, 2011): 955–63. https://doi.org/10.1007/s00521-010-0395-3.
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    • Huang, K., Y. Ying, and C. Campbell. “Generalized sparse metric learning with relative comparisons.” Knowledge and Information Systems 28, no. 1 (January 1, 2011): 25–45. https://doi.org/10.1007/s10115-010-0313-0.
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    • Huang, K., D. Zheng, J. Sun, Y. Hotta, K. Fujimoto, and S. Naoi. “Sparse learning for support vector classification.” Pattern Recognition Letters 31, no. 13 (October 1, 2010): 1944–51. https://doi.org/10.1016/j.patrec.2010.06.017.
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    • Xu, Zenglin, Kaizhu Huang, Jianke Zhu, Irwin King, and Michael R. Lyu. “A novel kernel-based maximum a posteriori classification method.” Neural Networks : The Official Journal of the International Neural Network Society 22, no. 7 (September 2009): 977–87. https://doi.org/10.1016/j.neunet.2008.11.005.
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    • Ying, Yiming, Kaizhu Huang, and Colin Campbell. “Enhanced protein fold recognition through a novel data integration approach.” Bmc Bioinformatics 10 (August 2009): 267. https://doi.org/10.1186/1471-2105-10-267.
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    • Yang, H., K. Huang, I. King, and M. R. Lyu. “Localized support vector regression for time series prediction.” Neurocomputing 72, no. 10–12 (June 1, 2009): 2659–69. https://doi.org/10.1016/j.neucom.2008.09.014.
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    • Huang, Kaizhu, Danian Zheng, Irwin King, and Michael R. Lyu. “Arbitrary norm support vector machines.” Neural Computation 21, no. 2 (February 2009): 560–82. https://doi.org/10.1162/neco.2008.12-07-667.
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    • Huang, K., H. Yang, I. King, and M. R. Lyu. “Maxi-min margin machine: learning large margin classifiers locally and globally.” Ieee Transactions on Neural Networks 19, no. 2 (February 2008): 260–72. https://doi.org/10.1109/tnn.2007.905855.
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    • Huang, Kaizhu, Haiqin Yang, Irwin King, and Michael R. Lyu. “Imbalanced learning with a biased minimax probability machine.” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 36, no. 4 (August 2006): 913–23. https://doi.org/10.1109/tsmcb.2006.870610.
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    • Huang, Kaizhu, Haiqin Yang, Irwin King, and Michael R. Lyu. “Maximizing sensitivity in medical diagnosis using biased minimax probability machine.” Ieee Transactions on Bio Medical Engineering 53, no. 5 (May 2006): 821–31. https://doi.org/10.1109/tbme.2006.872819.
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    • Huang, K., H. Yang, I. King, M. R. Lyu, and L. Chan. “The minimum error minimax probability machine.” Journal of Machine Learning Research 5 (October 1, 2004): 1253–86.

  • Book Sections

    • Ahmed, R., K. Dashtipour, M. Gogate, A. Raza, R. Zhang, K. Huang, A. Hawalah, A. Adeel, and A. Hussain. “Offline arabic handwriting recognition using deep machine learning: A review of recent advances,” 11691 LNAI:457–68, 2020. https://doi.org/10.1007/978-3-030-39431-8_44.
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    • Cao, Y., Q. F. Wang, K. Huang, and R. Zhang. “Improving image caption performance with linguistic context,” 11691 LNAI:3–11, 2020. https://doi.org/10.1007/978-3-030-39431-8_1.
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    • Hong, J., K. Huang, H. N. Liang, X. Wang, and R. Zhang. “Fine-grained image classification with object-part model,” 11691 LNAI:233–43, 2020. https://doi.org/10.1007/978-3-030-39431-8_22.
       Full Text
    • Li, J., Q. F. Wang, R. Zhang, and K. Huang. “Adversarial Rectification Network for Scene Text Regularization,” 12533 LNCS:152–63, 2020. https://doi.org/10.1007/978-3-030-63833-7_13.
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    • Pang, S., T. Ban, Y. Kadobayashi, J. Song, K. Huang, G. Poh, I. Gondal, K. Pasupa, and F. Aloul. “CDMC’19—The 10th International Cybersecurity Data Mining Competition,” 12533 LNCS:235–45, 2020. https://doi.org/10.1007/978-3-030-63833-7_20.
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    • Wang, Y., G. Zhong, Y. Mao, and K. Huang. “Feature Redirection Network for Few-Shot Classification,” 1332:418–25, 2020. https://doi.org/10.1007/978-3-030-63820-7_48.
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    • Xie, Y., J. Xiao, M. Sun, C. Yao, and K. Huang. “Feature Representation Matters: End-to-End Learning for Reference-Based Image Super-Resolution,” 12349 LNCS:230–45, 2020. https://doi.org/10.1007/978-3-030-58548-8_14.
       Full Text
    • Xu, H., X. Jin, Q. Wang, and K. Huang. “Multi-scale Attention Consistency for Multi-label Image Classification,” 1332:815–23, 2020. https://doi.org/10.1007/978-3-030-63820-7_93.
       Full Text
    • Yang, G., K. Huang, R. Zhang, J. Y. Goulermas, and A. Hussain. “Self-focus deep embedding model for coarse-grained zero-shot classification,” 11691 LNAI:12–22, 2020. https://doi.org/10.1007/978-3-030-39431-8_2.
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    • Zhang, Z., R. Zhang, Q. F. Wang, and K. Huang. “Improving disentanglement-based image-to-image translation with feature joint block fusion,” 11691 LNAI:540–49, 2020. https://doi.org/10.1007/978-3-030-39431-8_52.
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    • Zhong, G., X. Lin, K. Chen, Q. Li, and K. Huang. “Long short-term attention,” 11691 LNAI:45–54, 2020. https://doi.org/10.1007/978-3-030-39431-8_5.
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    • Wang, L. N., G. Zhong, S. Yan, J. Dong, and K. Huang. “Enhanced LSTM with batch normalization,” 11953 LNCS:746–55, 2019. https://doi.org/10.1007/978-3-030-36708-4_61.
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    • Jiang, H., G. Yang, K. Huang, and R. Zhang. “W-Net: One-shot arbitrary-style chinese character generation with deep neural networks,” 11305 LNCS:483–93, 2018. https://doi.org/10.1007/978-3-030-04221-9_43.
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    • Jiang, H., K. Huang, R. Zhang, and A. Hussain. “Style Neutralization Generative Adversarial Classifier,” 10989 LNAI:3–13, 2018. https://doi.org/10.1007/978-3-030-00563-4_1.
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    • Jiang, H., K. Huang, X. Y. Zhang, and R. Zhang. “Self-training field pattern prediction based on kernel methods.” In Semi-Supervised Learning: Background, Applications and Future Directions, 123–70, 2018.
    • Yao, K., K. Huang, R. Zhang, and A. Hussain. “Improving deep neural network performance with kernelized min-max objective,” 11301 LNCS:182–91, 2018. https://doi.org/10.1007/978-3-030-04167-0_17.
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    • Zhang, Y. M., K. Huang, G. G. Geng, and C. L. Liu. “Fast graph-based semi-supervised learning and its applications.” In Semi-Supervised Learning: Background, Applications and Future Directions, 67–98, 2018.
    • Jiang, H., K. Huang, and R. Zhang. “Field support vector regression,” 10634 LNCS:699–708, 2017. https://doi.org/10.1007/978-3-319-70087-8_72.
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    • Yang, X., K. Huang, and R. Zhang. “Deep mixtures of factor analyzers with common loadings: A novel deep generative approach to clustering,” 10634 LNCS:709–19, 2017. https://doi.org/10.1007/978-3-319-70087-8_73.
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    • Zhang, S., K. Huang, R. Zhang, and A. Hussain. “Improve deep learning with unsupervised objective,” 10634 LNCS:720–28, 2017. https://doi.org/10.1007/978-3-319-70087-8_74.
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    • Jin, X. B., G. G. Geng, K. Huang, and Z. W. Yan. “Statistical entity ranking with domain knowledge.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10102:811–18, 2016. https://doi.org/10.1007/978-3-319-50496-4_73.
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    • Wajid, S. K., A. Hussain, B. Luo, and K. Huang. “An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs),” 10023 LNAI:58–67, 2016. https://doi.org/10.1007/978-3-319-49685-6_6.
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    • Yang, X., K. Huang, R. Zhang, and A. Hussain. “Learning latent features with infinite non-negative binary matrix tri-factorization,” 9947 LNCS:587–96, 2016. https://doi.org/10.1007/978-3-319-46687-3_65.
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    • Zhang, S., and K. Huang. “Learning from few samples with memory network,” 9947 LNCS:606–14, 2016. https://doi.org/10.1007/978-3-319-46687-3_67.
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    • Cai, Y., G. Zhong, Y. Zheng, K. Huang, and J. Dong. “Is decaf good enough for accurate image classification?,” 9490:354–63, 2015. https://doi.org/10.1007/978-3-319-26535-3_41.
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    • Ting, T. O., X. S. Yang, S. Cheng, and K. Huang. “Hybrid metaheuristic algorithms: Past, present, and future.” In Studies in Computational Intelligence, 585:71–83, 2015. https://doi.org/10.1007/978-3-319-13826-8_4.
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    • Yang, C., X. C. Yin, and K. Huang. “Text categorization with diversity random forests,” 8836:317–24, 2014. https://doi.org/10.1007/978-3-319-12643-2_39.
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    • Yang, X., K. Huang, and R. Zhang. “Unsupervised dimensionality reduction for gaussian mixture model,” 8835:84–92, 2014. https://doi.org/10.1007/978-3-319-12640-1_11.
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    • Zhang, R., S. Zhang, and K. Huang. “A novel hybrid approach for combining deep and traditional neural networks,” 8836:349–56, 2014. https://doi.org/10.1007/978-3-319-12643-2_43.
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    • Yin, X. C., K. Huang, and H. W. Hao. “Dynamic ensemble of ensembles in nonstationary environments,” 8227 LNCS:76–83, 2013. https://doi.org/10.1007/978-3-642-42042-9_10.
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    • Zhang, R., and K. Huang. “One-side probability machine: Learning imbalanced classifiers locally and globally,” 8227 LNCS:140–47, 2013. https://doi.org/10.1007/978-3-642-42042-9_18.
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    • Zhang, Y. M., K. Huang, G. Geng, and C. L. Liu. “Fast kNN graph construction with locality sensitive hashing,” 8189 LNAI:660–74, 2013. https://doi.org/10.1007/978-3-642-40991-2_42.
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    • Zhong, G., K. Huang, X. Hou, and S. Xiang. “Local Tangent Space Laplacian Eigenmaps.” In Computational Intelligence, 17–34, 2012.
    • Liu, Y., X. Y. Zhang, K. Huang, X. Hou, and C. L. Liu. “Multiple Outlooks Learning with Support Vector Machines,” 7665 LNCS:116–24, 2012. https://doi.org/10.1007/978-3-642-34487-9_15.
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    • Yang, P., X. Y. Zhang, K. Huang, and C. L. Liu. “Manifold regularized multi-task learning,” 7665 LNCS:528–36, 2012. https://doi.org/10.1007/978-3-642-34487-9_64.
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    • Yin, X. C., K. Huang, H. W. Hao, K. Iqbal, and Z. B. Wang. “Classifier ensemble using a heuristic learning with sparsity and diversity,” 7664 LNCS:100–107, 2012. https://doi.org/10.1007/978-3-642-34481-7_13.
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    • Yang, P., K. Huang, and C. L. Liu. “Geometry preserving multi-task metric learning,” 7523 LNAI:648–64, 2012. https://doi.org/10.1007/978-3-642-33460-3_47.
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    • Xu, B., K. Huang, I. King, C. L. Liu, J. Sun, and N. Satoshi. “Graphical lasso quadratic discriminant function for character recognition,” 7064 LNCS:747–55, 2011. https://doi.org/10.1007/978-3-642-24965-5_84.
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    • Yang, P., K. Huang, and C. L. Liu. “Multi-task low-rank metric learning based on common subspace,” 7063 LNCS:151–59, 2011. https://doi.org/10.1007/978-3-642-24958-7_18.
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    • Zhong, G., K. Huang, and C. L. Liu. “Learning ECOC and dichotomizers jointly from data,” 6443 LNCS:494–502, 2010. https://doi.org/10.1007/978-3-642-17537-4_61.
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    • Wang, Z. B., H. W. Hao, X. C. Yin, Q. Liu, and K. Huang. “Exchange rate forecasting using classifier ensemble,” 5863 LNCS:884–91, 2009. https://doi.org/10.1007/978-3-642-10677-4_100.
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    • Yin, X. C., Q. Liu, H. W. Hao, Z. B. Wang, and K. Huang. “A rock structure recognition system using FMI images,” 5863 LNCS:838–45, 2009. https://doi.org/10.1007/978-3-642-10677-4_95.
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    • Xu, Z., K. Huang, J. Zhu, I. King, and M. R. Lyu. “Kernel maximum a posteriori classification with error bound analysis,” 4984 LNCS:841–50, 2008. https://doi.org/10.1007/978-3-540-69158-7_87.
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    • Huang, K., Z. Xu, I. King, M. R. Lyu, and Z. Zhou. “A novel discriminative naive Bayesian network for classification.” In Bayesian Network Technologies: Applications and Graphical Models, 1–12, 2007. https://doi.org/10.4018/978-1-59904-141-4.ch001.
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    • Huang, K., J. Sun, Y. Hotta, K. Fujimoto, S. Naoi, C. Long, L. Zhuang, and X. Zhu. “A hybrid handwritten chinese address recognition approach,” 4233 LNCS-II:88–98, 2006. https://doi.org/10.1007/11893257_10.
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    • Yang, H., K. Huang, L. Chan, I. King, and M. R. Lyu. “Outliers treatment in support vector regression for financial time series prediction,” 3316:1260–65, 2004. https://doi.org/10.1007/978-3-540-30499-9_196.
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    • Huang, K., I. King, and M. R. Lyu. “Finite mixture model of bounded semi-naive bayesian networks classifier,” 2714:115–22, 2003. https://doi.org/10.1007/3-540-44989-2_15.
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  • Conference Papers

    • Guo, J., K. Huang, X. Yi, and R. Zhang. “Graph Neural Networks with Diverse Spectral Filtering.” In Acm Web Conference 2023  Proceedings of the World Wide Web Conference, Www 2023, 306–16, 2023. https://doi.org/10.1145/3543507.3583324.
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    • Yao, K., P. Gao, X. Yang, J. Sun, R. Zhang, and K. Huang. “Outpainting by Queries.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13683 LNCS:153–69, 2022. https://doi.org/10.1007/978-3-031-20050-2_10.
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    • Wang, K., J. Ma, K. L. Man, D. Hong, K. Huang, and X. Huang. “Real-time Modeling of Photovoltaic Strings under Partial Shading Conditions.” In Proceedings of 2021 Ieee 10th Data Driven Control and Learning Systems Conference, Ddcls 2021, 1345–49, 2021. https://doi.org/10.1109/DDCLS52934.2021.9455638.
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    • Lyu, Q., Q. F. Wang, and K. Huang. “High-Resolution Virtual Try-On Network with Coarse-to-Fine Strategy.” In Journal of Physics: Conference Series, Vol. 1880, 2021. https://doi.org/10.1088/1742-6596/1880/1/012009.
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    • Zhang, Z., X. Yang, and K. Huang. “Attacking Sequential Learning Models with Style Transfer Based Adversarial Examples.” In Journal of Physics: Conference Series, Vol. 1880, 2021. https://doi.org/10.1088/1742-6596/1880/1/012021.
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    • Li, J., Q. F. Wang, R. Zhang, and K. Huang. “Mix-Up Augmentation for Oracle Character Recognition with Imbalanced Data Distribution.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12821 LNCS:237–51, 2021. https://doi.org/10.1007/978-3-030-86549-8_16.
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    • Ning, M., Q. F. Wang, K. Huang, and X. Huang. “A Segment-Based Layout Aware Model for Information Extraction on Document Images.” In Communications in Computer and Information Science, 1516 CCIS:757–65, 2021. https://doi.org/10.1007/978-3-030-92307-5_88.
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    • Shi, L., L. Yu, K. Huang, X. Zhu, Z. Wang, X. Li, W. Wang, and X. Wang. “A Covert Ultrasonic Phone-to-Phone Communication Scheme.” In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Lnicst, 349:36–48, 2021. https://doi.org/10.1007/978-3-030-67537-0_3.
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    • Yang, G., K. Huang, R. Zhang, J. Y. Goulermas, and A. Hussain. “Inductive Generalized Zero-Shot Learning with Adversarial Relation Network.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12458 LNAI:724–39, 2021. https://doi.org/10.1007/978-3-030-67661-2_43.
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    • Chen, Q., W. Wang, K. Huang, S. De, and F. Coenen. “Adversarial Domain Adaptation for Crisis Data Classification on Social Media.” In Proceedings  Ieee Congress on Cybermatics: 2020 Ieee International Conferences on Internet of Things, Ithings 2020, Ieee Green Computing and Communications, Greencom 2020, Ieee Cyber, Physical and Social Computing, Cpscom 2020 and Ieee Smart Data, Smartdata 2020, 282–87, 2020. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00061.
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    • Jiang, C., K. Huang, S. Zhang, X. Wang, and J. Xiao. “Pay Attention Selectively and Comprehensively: Pyramid Gating Network for Human Pose Estimation without Pre-training.” In Mm 2020  Proceedings of the 28th Acm International Conference on Multimedia, 2364–71, 2020. https://doi.org/10.1145/3394171.3414041.
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    • Chen, Q., W. Wang, K. Huang, S. De, and F. Coenen. “Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media.” In Proceedings  2020 Ieee International Conference on Smart Computing, Smartcomp 2020, 232–37, 2020. https://doi.org/10.1109/SMARTCOMP50058.2020.00051.
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    • Luo, Y., and K. Huang. “Super-resolving Tiny Faces with Face Feature Vectors.” In 10th International Conference on Information Science and Technology, Icist 2020, 145–52, 2020. https://doi.org/10.1109/ICIST49303.2020.9202156.
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    • Wang, K., D. Hong, J. Ma, K. L. Man, K. Huang, and X. Huang. “Maximum Power Point Tracking of Photovoltaic Systems Using Deep Q-networks.” In Ieee International Conference on Industrial Informatics (Indin), 2020-July:100–103, 2020. https://doi.org/10.1109/INDIN45582.2020.9442100.
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    • Cheng, J., K. Huang, and Z. Zheng. “Towards better forecasting by fusing near and distant future visions.” In Aaai 2020  34th Aaai Conference on Artificial Intelligence, 3593–3600, 2020.
    • Fang, Y., R. Zhang, Q. F. Wang, and K. Huang. “Action recognition in videos with temporal segments fusions.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11691 LNAI:244–53, 2020. https://doi.org/10.1007/978-3-030-39431-8_23.
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    • Mao, Y., G. Zhong, H. Wang, and K. Huang. “MCRN: A New Content-Based Music Classification and Recommendation Network.” In Communications in Computer and Information Science, 1332:771–79, 2020. https://doi.org/10.1007/978-3-030-63820-7_88.
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    • Zhang, B., J. Xiao, Y. Wei, M. Sun, and K. Huang. “Reliability does matter: An end-to-end weakly supervised semantic segmentation approach.” In Aaai 2020  34th Aaai Conference on Artificial Intelligence, 12765–72, 2020.
    • Gogate, M., A. Hussain, and K. Huang. “Random features and random neurons for brain-inspired big data analytics.” In Ieee International Conference on Data Mining Workshops, Icdmw, 2019-November:522–29, 2019. https://doi.org/10.1109/ICDMW.2019.00080.
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    • He, L., Z. Guo, K. Huang, and Z. Xu. “Deep minimax probability machine.” In Ieee International Conference on Data Mining Workshops, Icdmw, 2019-November:869–76, 2019. https://doi.org/10.1109/ICDMW.2019.00127.
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    • Xiong, F., Z. Liu, K. Huang, X. Yang, and A. Hussain. “Primitives generation policy learning without catastrophic forgetting for robotic manipulation.” In Ieee International Conference on Data Mining Workshops, Icdmw, 2019-November:890–97, 2019. https://doi.org/10.1109/ICDMW.2019.00130.
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    • Yang, X., Y. Yan, K. Huang, and R. Zhang. “VSB-DVM: An end-to-end bayesian nonparametric generalization of deep variational mixture model.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2019-November:688–97, 2019. https://doi.org/10.1109/ICDM.2019.00079.
       Full Text
    • Zhang, S., K. Huang, R. Zhang, and A. Hussain. “Generalized adversarial training in riemannian space.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2019-November:826–35, 2019. https://doi.org/10.1109/ICDM.2019.00093.
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    • Zhang, S., Z. Qian, K. Huang, R. Zhang, and A. Hussain. “SimpleGAN: Stabilizing generative adversarial networks with simple distributions.” In Ieee International Conference on Data Mining Workshops, Icdmw, 2019-November:905–10, 2019. https://doi.org/10.1109/ICDMW.2019.00132.
       Full Text
    • Jin, X. B., G. S. Xie, K. Huang, J. Miao, and Q. Wang. “Beyond attributes: High-order attribute features for zero-shot learning.” In Proceedings  2019 International Conference on Computer Vision Workshop, Iccvw 2019, 2953–62, 2019. https://doi.org/10.1109/ICCVW.2019.00357.
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    • Zhou, L., Q. F. Wang, K. Huang, and C. H. Lo. “An interactive and generative approach for Chinese Shanshui painting document.” In Proceedings of the International Conference on Document Analysis and Recognition, Icdar, 819–24, 2019. https://doi.org/10.1109/ICDAR.2019.00136.
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    • Qu, S., K. Huang, A. Hussain, and Y. Goulermas. “MPSSD: Multi-Path Fusion Single Shot Detector.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2019-July, 2019. https://doi.org/10.1109/IJCNN.2019.8852053.
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    • Gao, Z., D. Liu, K. Huang, and Y. Huang. “Mining human activity and smartphone position from motion sensors.” In International Conference on Intelligent User Interfaces, Proceedings Iui, 17–18, 2019. https://doi.org/10.1145/3308557.3308681.
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    • Dong, H., W. Wang, K. Huang, and F. Coenen. “Joint multi-label attention networks for social text annotation.” In Naacl Hlt 2019  2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies  Proceedings of the Conference, 1:1348–54, 2019.
    • Naserian, E., X. Wang, X. Xu, Y. Dong, N. Georgalas, and K. Huang. “Integrated discovery of location prediction rules in mobile environment.” In Proceedings  2017 Ieee 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 Ieee 15th International Conference on Pervasive Intelligence and Computing, 2017 Ieee 3rd International Conference on Big Data Intelligence and Computing and 2017 Ieee Cyber Science and Technology Congress, Dasc Picom Datacom Cyberscitec 2017, 2018-January:1017–24, 2018. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2017.167.
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    • Wajid, S. K., A. Hussain, K. Huang, and W. Boulila. “Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques.” In Proceedings of 2016 Ieee 15th International Conference on Cognitive Informatics and Cognitive Computing, Icci*Cc 2016, 359–66, 2017. https://doi.org/10.1109/ICCI-CC.2016.7862060.
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    • Lyu, C., K. Huang, and H. N. Liang. “A unified gradient regularization family for adversarial examples.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2016-January:301–9, 2016. https://doi.org/10.1109/ICDM.2015.84.
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    • Yang, X., K. Huang, R. Zhang, and J. Y. Goulermas. “Two-layer Mixture of Factor Analyzers with Joint Factor Loading.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2015-September, 2015. https://doi.org/10.1109/IJCNN.2015.7280350.
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    • Huang, K., H. Yang, I. King, and M. R. Lyu. “WSDM'15 workshop summary / scalable data analytics:Theory and applications.” In Wsdm 2015  Proceedings of the 8th Acm International Conference on Web Search and Data Mining, 425–26, 2015. https://doi.org/10.1145/2684822.2697030.
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    • Loo, C. K., K. S. Yap, K. W. Wong, A. Teoh, and K. Huang. “Preface.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8836:IV–VI, 2014.
    • Zhang, X. Y., K. Huang, and C. L. Liu. “Feature transformation with class conditional decorrelation.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 887–96, 2013. https://doi.org/10.1109/ICDM.2013.43.
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    • Farooq, K., P. Yang, A. Hussain, K. Huang, C. Macrae, C. Eckl, and W. Slack. “Efficient clinical decision making by learning from missing clinical data.” In Proceedings of the 2013 Ieee Symposium on Computational Intelligence in Healthcare and E Health, Cicare 2013  2013 Ieee Symposium Series on Computational Intelligence, Ssci 2013, 27–33, 2013. https://doi.org/10.1109/CICARE.2013.6583064.
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    • Yin, X. C., X. Yin, K. Huang, and H. W. Hao. “Accurate and robust text detection: A step-in for text retrieval in natural scene images.” In Sigir 2013  Proceedings of the 36th International Acm Sigir Conference on Research and Development in Information Retrieval, 1091–92, 2013. https://doi.org/10.1145/2484028.2484197.
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    • Tao, D., Z. Li, J. Li, A. Katsaggelos, W. Bian, Y. Chen, J. Fan, et al. “Preface.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2011. https://doi.org/10.1109/ICDMW.2011.199.
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    • Zhang, X. Y., K. Huang, and C. L. Liu. “Pattern field classification with style normalized transformation.” In Ijcai International Joint Conference on Artificial Intelligence, 1621–26, 2011. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-272.
       Full Text
    • Zhang, Y. M., K. Huang, and C. L. Liu. “Fast and robust graph-based transductive learning via minimum tree cut.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 952–61, 2011. https://doi.org/10.1109/ICDM.2011.66.
       Full Text
    • Zhong, G., K. Huang, and C. L. Liu. “Low rank metric learning with manifold regularization.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 1266–71, 2011. https://doi.org/10.1109/ICDM.2011.95.
       Full Text
    • Xu, B., K. Huang, and C. L. Liu. “Similar handwritten Chinese characters recognition by critical region selection based on average symmetric uncertainty.” In Proceedings  12th International Conference on Frontiers in Handwriting Recognition, Icfhr 2010, 527–32, 2010. https://doi.org/10.1109/ICFHR.2010.87.
       Full Text
    • Xu, B., K. Huang, and C. L. Liu. “Dimensionality reduction by minimal distance maximization.” In Proceedings  International Conference on Pattern Recognition, 569–72, 2010. https://doi.org/10.1109/ICPR.2010.144.
       Full Text
    • Huang, K., R. Jin, Z. Xu, and C. L. Liu. “Robust metric learning by smooth optimization.” In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, Uai 2010, 244–51, 2010.
    • Huang, K., Y. Ying, and C. Campbell. “GSML: A unified framework for sparse metric learning.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 189–98, 2009. https://doi.org/10.1109/ICDM.2009.22.
       Full Text
    • Ying, Y., K. Huang, and C. Campbell. “Sparse metric learning via smooth optimization.” In Advances in Neural Information Processing Systems 22  Proceedings of the 2009 Conference, 2214–22, 2009.
    • Huang, K., Z. Xu, I. King, M. R. Lyu, and C. Campbell. “Supervised Self-taught Learning: Actively transferring knowledge from unlabeled data.” In Proceedings of the International Joint Conference on Neural Networks, 1272–77, 2009. https://doi.org/10.1109/IJCNN.2009.5178647.
       Full Text
    • Huang, K., I. King, and M. R. Lyu. “Direct zero-norm optimization for feature selection.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 845–50, 2008. https://doi.org/10.1109/ICDM.2008.60.
       Full Text
    • Huang, K., Z. Xu, I. King, and M. R. Lyu. “Semi-supervised learning from general unlabeled data.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 273–82, 2008. https://doi.org/10.1109/ICDM.2008.61.
       Full Text
    • Xu, Z., R. Jin, K. Huang, M. R. Lyu, and I. King. “Semi-supervised text categorization by active search.” In International Conference on Information and Knowledge Management, Proceedings, 1517–18, 2008. https://doi.org/10.1145/1458082.1458364.
       Full Text
    • Yang, H., K. Huang, I. King, and M. R. Lyu. “Efficient minimax clustering probability machine by generalized probability product kernel.” In Proceedings of the International Joint Conference on Neural Networks, 4014–19, 2008. https://doi.org/10.1109/IJCNN.2008.4634375.
       Full Text
    • Zhou, Z., S. Bhiri, L. Shu, L. Vasiliu, M. Hauswirth, and K. Huang. “A scenario-view based approach to analyze external behavior of web services for supporting mediated service interactions.” In Proceedings  2008 Ieee International Conference on Services Computing, Scc 2008, 2:249–56, 2008. https://doi.org/10.1109/SCC.2008.41.
       Full Text
    • Huang, K., J. Sun, Y. Hotta, K. Fujimoto, and S. Naoi. “An SVM-based high-accurate recognition approach for handwritten numerals by using difference features.” In Proceedings of the International Conference on Document Analysis and Recognition, Icdar, 2:589–93, 2007. https://doi.org/10.1109/ICDAR.2007.4376983.
       Full Text
    • Sun, J., K. Huang, Y. Hotta, K. Fujimoto, and S. Naoi. “Degraded character recognition by complementary classifiers combination.” In Proceedings of the International Conference on Document Analysis and Recognition, Icdar, 2:579–83, 2007. https://doi.org/10.1109/ICDAR.2007.4376981.
       Full Text
    • Huang, K., H. Yang, I. King, and M. R. Lyu. “Local support vector regression for financial time series prediction.” In Ieee International Conference on Neural Networks  Conference Proceedings, 1622–27, 2006.
    • Long, C., X. Zhu, K. Huang, J. Sun, Y. Hotta, and S. Naoi. “An efficient post-processing approach for off-line handwritten Chinese address recognition.” In International Conference on Signal Processing Proceedings, Icsp, Vol. 2, 2006. https://doi.org/10.1109/ICOSP.2006.345728.
       Full Text
    • Hoi, C. H., C. H. Chan, K. Huang, M. R. Lyu, and I. King. “Biased support vector machine for relevance feedback in image retrieval.” In Ieee International Conference on Neural Networks  Conference Proceedings, 4:3189–94, 2004.
    • Huang, K., H. Yang, I. King, and M. R. Lyu. “Learning large margin classifiers locally and globally.” In Proceedings, Twenty First International Conference on Machine Learning, Icml 2004, 401–8, 2004.
    • Huang, K., H. Yang, I. King, and M. R. Lyu. “Learning classifiers from imbalanced data based on biased minimax probability machine.” In Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, 2004.
    • Huang, K., I. King, and M. R. Lyu. “Discriminative Training of Bayesian Chow-Liu Multinet Classifiers.” In Proceedings of the International Joint Conference on Neural Networks, 1:484–88, 2003.
    • Huang, K., I. King, and M. R. Lyu. “Constructing a large node Chow-Liu tree based on frequent itemsets.” In Iconip 2002  Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E Age, 1:498–502, 2002. https://doi.org/10.1109/ICONIP.2002.1202220.
       Full Text
    • Huang, K., I. King, and M. R. Lyu. “Learning maximum likelihood semi-naive Bayesian network classifier.” In Proceedings of the Ieee International Conference on Systems, Man and Cybernetics, 3:306–10, 2002.
• Teaching & Mentoring
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  Recent Courses

  • ECE 586K: Vector Space Methods with Applications 2023
  • ECE 590K: Advanced Topics in Electrical and Computer Engineering 2023
  • K_CAPST 496: Signature Work Capstone II 2023
  • K_ECE 590K: ADVANCED TOPICS IN ECE 2023
  • ECE 586K: Vector Space Methods with Applications 2022
  • ECE 590K: Advanced Topics in Electrical and Computer Engineering 2022

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