Huanhuan Chen – Publications

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Journal Papers

• Ao Chen, Xiren Zhou, Yizhan Fan, Huanhuan Chen. Underground Diagnosis Based on GPR and Learning in the Model Space. IEEE Transactions on Pattern Analysis and Machine Intelligence, Accepted, 2023.


• Xiangyu Wang, Taiyu Ban, Lyuzhou Chen, Muhammad Usman, Yifeng Guan, Derui Lyu, Jian Cheng, Huanhuan Chen, Cyril Leung,and Chunyan Miao. Decentralised Knowledge Graph Evolution via Blockchain. IEEE Transactions on Services Computing, DOI: 10.1109/TSC.2023.3337873, 2023.


• Xiangyu Wang, Lyuzhou Chen, Taiyu Ban, Derui Lyu, Yifeng Guan, Xingyu Wu, Xiren Zhou, Huanhuan Chen. Accurate Label Refinement from Multi-Annotator of Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2023.3241402, 2023.


• Xingyu Wu, Bingbing Jiang, Xiangyu Wang, Taiyu Ban, Huanhuan Chen. Feature Selection in the Data Stream Based on Incremental Markov Boundary Learning. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2023.3249767, 2023.


• Xin Wang, Shengfei Lyu, Xiangyu Wang, Xingyu Wu, Huanhuan Chen. Temporal Knowledge Graph Embedding via Sparse Transfer Matrix. Information Sciences, 623:56–69, 2023.


• Lei Li, Minghe Xue, Zan Zhang, Huanhuan Chen, Xindong Wu. "Certainty-based Preference Completion". Data Intelligence, 4: 112-133, 2022.


• Xiangyu Wang, Taiyu Ban, Lyuzhou Chen, Xingyu Wu, Derui Lyu, Huanhuan Chen. Knowledge Verification from Data. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3202244, 2022.


• Xingyu Wu, Zhenchao Tao, Bingbing Jiang, Tianhao Wu, Xin Wang, Huanhuan Chen. "Domain knowledge-enhanced variable selection for biomedical data analysis". Information Sciences, 606: 469-488, 2022.


• Bingbing Jiang, Junhao Xiang, Xingyu Wu, Yadi Wang, Huanhuan Chen, Weiwei Cao, Weiguo Sheng. "Robust multi-view learning via adaptive regression". Information Sciences, 610: 916-937, 2022.


• Xiren Zhou, Qiuju Chen, Shengfei Lyu, Huanhuan Chen: "Ellipse Inversion Model for Estimating the Orientation and Radius of Pipes From GPR Image". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15: 8299-8308, 2022.


• Xingyu Wu, Bingbing Jiang, Yan Zhong and Huanhuan Chen. "Multi-target Markov Boundary Discovery: Theory, Algorithm, and Application" IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022.


• Buliao Huang, Yunhui Zhu, Muhammad Usman, Xiren Zhou, and Huanhuan Chen. "Graph Neural Networks for Missing Value Classification in a Task-driven Metric Space" IEEE Transactions on Knowledge and Data Engineering, 2022. DOI: 10.1109/TKDE.2022.3198689


• Xiren Zhou , Qiuju Chen , Bingbing Jiang, and Huanhuan Chen. "An Underground Pipeline Mapping Method based on Fusion of Multi-Source Data" IEEE Transactions on Geoscience and Remote Sensing, 2022. DOI: 10.1109/TGRS.2022.3200153


• Bingbing Jiang, Xingyu Wu, Xiren Zhou, Yi Liu, Anthony Cohn, Weiguo Sheng and Huanhuan Chen. "Semi-Supervised Multi-View Feature Selection with Adaptive Graph Learning" IEEE Transactions on Neural Networks and Learning Systems, 2022.


• Taiyu Ban, Xiangyu Wang, Lyuzhou Chen, Xingyu Wu, Qiuju Chen, and Huanhuan Chen. "Quality Evaluation of Triples in Knowledge Graph by Incorporating Internal with External Consistency" IEEE Transactions on Neural Networks and Learning Systems, 2022.


• Lyuzhou Chen, Xiangyu Wang, Taiyu Ban, Muhammad Usman, Shikang Liu, Derui Lyu and Huanhuan Chen. "Research Ideas Discovery via Hierarchical Negative Correlation" IEEE Transactions on Neural Networks and Learning Systems, 2022.


• Xiren Zhou , Qiuju Chen , Shengfei Lyu and Huanhuan Chen. "Mapping the Buried Cable by Ground Penetrating Radar and Gaussian-Process Regression" IEEE Transactions on Geoscience and Remote Sensing, 2022.


• Shengfei Lyu, Xingyu Wu, Jinlong Li, Qiuju Chen and Huanhuan Chen. "Do Models Learn the Directionality of Relations? A New Evaluation: Relation Direction Recognition" IEEE Transactions on Emerging Topics in Computational Intelligence, 2022.


• Lei Li, Mengjiao Yan, Zhenchao Tao, Huanhuan Chen and Xindong Wu. "Semi-Supervised Graph Pattern Matching and Rematching for Expert Community Location" ACM Transactions on Knowledge Discovery from Data, 2022.


• Gangqiang Hu, Shengfei Lyu, Xingyu Wu, Jinlong Li and Huanhuan Chen. "Contextual-Aware Information Extractor with Adaptive Objective for Chinese Medical Dialogues" ACM Transactions on Asian and Low-Resource Language Information Processing, 2022.


• Xingyu Wu, Bingbing Jiang, Kui Yu and Huanhuan Chen. "Separation and recovery Markov boundary discovery and its application in EEG-based emotion recognition". Information Sciences, 2021, 571: 262-278.


• Caijun Ren, Xiangyu Wang, Jian Gao, Xiren Zhou and Huanhuan Chen. "Unsupervised change detection in satellite images with generative adversarial network". IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(12):10047-10061.


• Weibo Shu, Yaqiang Yao, Shengfei Lyu, Jinlong Li and Huanhuan Chen. "Short isometric shapelet transform for binary time series classification". Knowledge and Information Systems, 2021, 8:1-29.


• Yunhui Zhu, Buliao Huang, Jian Gao, Enxing Huang and Huanhuan Chen. "Adaptive Polygon Generation Algorithm for Automatic Building Extraction". IEEE Transactions on Geoscience and Remote Sensing, 2021, 60:4702114.


• Xuejiao Zhao, Huanhuan Chen, Zhenchang Xing and Chunyan Miao. "Brain-Inspired Search Engine Assistant Based on Knowledge Graph". IEEE Transactions on Neural Networks and Learning Systems, 2021, DOI:10.1109/TETCI.2021.3067017.


• Lei Li, Ping Ding, Huanhuan Chen and Xindong Wu. "Frequent Pattern Mining in Big Social Graphs". IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, DOI:10.1109/TNNLS.2021.3113026.


• Yuyao Wang, Jie Cao, Zhan Bu, Jiuchuan Jiang and Huanhuan Chen. "Proximity-based group formation game model for community detection in social network". Knowledge-Based Systems, 2021, 214: 106670.


• Xinyan Zhao, Liangwei Chen and Huanhuan Chen."A Weighted Heterogeneous Graph-Based Dialog System". IEEE Transactions on Neural Networks and Learning Systems, 2021. (Accepted)


• Xinyan Zhao, Xiao Feng and Huanhuan Chen."A Background Knowledge Revising and Incorporating Dialogue Model". IEEE Transactions on Neural Networks and Learning Systems, 2021. (Accepted)


• Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu . "Subarchitecture Ensemble Pruning in Neural Architecture Search". IEEE Transactions on Neural Networks and Learning Systems, 2021. (Accepted)


• Yijun Bian and Huanhuan Chen. "When does Diversity Help Generalization in Classification Ensembles?". IEEE Transactions on Cybernetics, 2021.


• Weijie Zheng, Huanhuan Chen, and Xin Yao. "Analysis of Evolutionary Algorithms on Fitness Function with Time-linkage Property". IEEE Transactions on Evolutionary Computation, 2021.


• Yaqiang Yao, Yang Li, Bingbing Jiang, and Huanhuan Chen. "Multiple Kernel k-Means Clustering by Selecting Representative Kernels." IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2020.3026532, 2020.


• Peng Zhang, Jinlong Li, Tengfei Li, and Huanhuan Chen. "A New Many-Objective Evolutionary Algorithm Based on Determinantal Point Processes." IEEE Transactions on Evolutionary Computation, DOI: 10.1109/TEVC.2020.3035825, 2020.


• Xinyu Wu, Bingbing Jiang, Kui Yu, Chunyan Miao, and Huanhuan Chen. "Accurate Markov Boundary Discovery for Causal Feature Selection." IEEE Transactions on Cybernetics, vol. 50, no. 12, pp. 4983-4996, Dec. 2020.


• Yijun Bian, Yijun Wang, Yaqiang Yao, and Huanhuan Chen. "Ensemble Pruning based on Objection Maximization with a General Distributed Framework." IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3766-3774, Sept. 2020.


• Bo Yuan, Huanhuan Chen and Xin Yao. "Toward Efficient Design Space Exploration for Fault-tolerant Multiprocessor Systems." IEEE Transactions on Evolutionary Computation, vol. 24, no. 1, pp. 157-169, Feb. 2020.


• Shengfei Lyu, Xing Tian, Yang Li, Bingbing Jiang and Huanhuan Chen. "Multi-class Probabilistic Classification Vector Machines." IEEE Transactions on Neural Networks and Learning Systems, 31(10):3906-3919, 2019.


• Xiren Zhou, Huanhuan Chen and Jinlong Li. "Probabilistic Mixture Model for Mapping the Underground Pipes." ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Knowledge Discovery from Data (TKDD), 13(5), 1-26.2019.


• Guiping Jiang, Xiren Zhou, Jinlong Li, and Huanhuan Chen. "A Cable-Mapping Algorithm Based on Ground-Penetrating Radar." IEEE Geoscience and Remote Sensing Letters, 16(10):1630-1634, 2019.


• Yang Li, Junyuan Hong, Huanhuan Chen. "Short Sequence Classification through Discriminable Linear Dynamical System." IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 11, pp. 3396-3408, Nov. 2019.


• Xiren Zhou, Huanhuan Chen, Tong Hao. "Efficient Detection of Buried Plastic Pipes by Combining GPR and Electric-field Methods" IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 6, pp. 3967-3979, June 2019.


• Bingbing Jiang, Chang Li, Maarten de Rijke, Xin Yao, Huanhuan Chen. "Probabilistic Feature Selection and Classification Vector Machine." ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Knowledge Discovery from Data (TKDD), 13(2), 1-27.2019.


• Junyuan Hong, Yang Li, Huanhuan Chen. "Variant Grassmann Manifolds: a Representation Augmentation Method for Action Recognition." ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Knowledge Discovery from Data (TKDD), 13(2), 1-23.2019.


• Zhichen Gong, Huanhuan Chen, Bo Yuan, and Xin Yao, "Multiobjective Learning in the Model Space for Time Series Classification." IEEE Transactions on Cybernetics, vol. 49, no. 3, pp. 918-932, March 2019.


• Yang Li, Bingbing Jiang, Huanhuan Chen, and Xin Yao. "Symbolic Sequence Classification in the Fractal Space." IEEE Transactions on Emerging Topics in Computational Intelligence.


• Kui Yu, Lin Liu, Jiuyong Li, and Huanhuan Chen "Mining Markov Blankets without Causal Sufficiency." IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6333-6347, Dec. 2018.


• Yaqiang Yao, Yan Liu, Zhenyu Liu Huanhuan Chen. "Human Activity Recognition with Posture Tendency Descriptors on Action Snippets." IEEE Transactions on Big Data, 10.1109/TBDATA.2018.2803838.


• Bingbing Jiang, Zhengyu Li, Huanhuan Chen, Anthony Cohn. "Latent Topic Text Representation Learning on Statistical Manifolds." IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2018.2808332.


• Rodrigo Soares, Huanhuan Chen, Xin Yao. "Efficient Cluster-based Boosting for Semi-supervised Classification." IEEE Transactions on Neural Networks and Learning Systems, 10.1109/TNNLS.2018.2809623.2018.


• Kui Yu, Huanhuan Chen. "Markov boundary-based outlier Mining." IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 4, pp. 1259-1264, April 2019.


• Xiren Zhou, Huanhuan Chen, Jinlong Li, "An Automatic GPR B-scan Image Interpreting Model." IEEE Transactions on Geoscience and Remote Sensing,vol. 56, no. 6, pp. 3398-3412, June 2018.


• Huanhuan Chen, Bingbing Jiang, and Xin Yao, "Semi-supervised Negative Correlation Learning." IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 11, pp. 5366-5379, Nov. 2018.


• Zhichen Gong, Huanhuan Chen, "Sequential Data Classification by Dynamic State Warping." Knowledge and Information Systems,57(3), 545-570.


• Bingbing Jiang, Huanhuan Chen, Bo Yuan, Xin Yao, "Scalable Graph-Based Semi-Supervised Learning Through Sparse Bayesian Model." IEEE Transactions on Knowledge and Data Engineering, 29(12):2758 - 2771, 2017.


• Rodrigo G. F. Soares, Huanhuan Chen, Xin Yao, "A Cluster-based Semi-supervised Ensemble for Multi-class Classification." IEEE Transactions on Emerging Topics in Computational Intelligence, 1(6):408 - 420, 2017.


• Bo Yuan, Huanhuan Chen, Xin Yao, "Optimal Relay Placement for Lifetime Maximization in Wireless Underground Sensor Networks." Information Sciences, vol. 418-419, pp. 463-479, 2017.


• Ke Liu, Dunwei Gong, Fanlin Meng, Huanhuan Chen, Gai-Ge Wang, "Gesture segmentation based on a two-phase estimation of distribution algorithm." Information Sciences, vol. 394, pp. 88-105, 2017.


• Xindong Wu, Huanhuan Chen, Jun Liu, Gong-Qing Wu, Ruqian Lu, Nanning Zheng, "Knowledge Engineering With Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project." IEEE Access, vol. 5, pp. 12696-12701, 2017.


• Wei Fang, Jun Sun, Huanhuan Chen, Xiaojun Wu. "A decentralized quantum-inspired particle swarm optimization algorithm with cellular structured population." Information Sciences, 330:19–48, 2016.


• Xindong Wu, Huanhuan Chen, Gong-Qing Wu, etc. "Knowledge Engineering with Big Data." IEEE Intelligent Systems, 30(5):46-55, 2015.


• FengZhen Tang, Peter Tino, Pedro A.G. Pena, Huanhuan Chen. "The Benefits of Modelling Slack Variables in SVMs." Neural Computation, 27(4):954-81, 2015.


• Shan He, Huanhuan Chen, Zexuan Zhu, etc. "Robust Twin Boosting for Feature Selection from High-dimensional Omics Data with Label Noise." Information Science, 291:1–18, 2015.


• Bo Yuan,Bin Li,Huanhuan Chen,Xin Yao."A New Evolutionary Algorithm with Structure Mutation for the Maximum Balanced Biclique Problem."IEEE Transactions on Cybernetics, 45(5):1040-1053, 2015.


• Huanhuan Chen, Peter Tiňo, Xin Yao. "Cognitive Fault Diagnosis in Tennessee Eastman Process using Learning in the Model Space." Computers & Chemical Engineering, 2014. Available online or [here]


• Huanhuan Chen, Peter Tino, Ali Rodan, Xin Yao. "Learning in the Model Space for Cognitive Fault Diagnosis." IEEE Transactions on Neural Networks and Learning Systems, 25(1):124-136, 2014. Available [here]


• Huanhuan Chen, Peter Tino, Xin Yao. "Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection." IEEE Transactions on Neural Networks and Learning Systems, 25(2):356-369, 2014. Available [here]


• Huanhuan Chen, Xin Yao. "Multiobjective Neural Network Ensembles Based on Regularized Negative Correlation Learning." IEEE Transactions Knowledge Data Engineering, 22(12):1738-1751, 2010. Available [here]


• Huanhuan Chen, Peter Tiño, Xin Yao. "Predictive Ensemble Pruning by Expectation Propagation." IEEE Transactions Knowledge Data Engineering, 21(7): 999-1013, 2009. Available [here]


• Huanhuan Chen, Peter Tino, Xin Yao. "Probabilistic Classification Vector Machines." IEEE Transactions on Neural Networks , 20(6): 901-914 (2009).
  (IEEE Transactions on Neural Networks Outstanding 2009 Paper Award (bestowed in 2011)). Available [here]
  Matlab software Availablehere


• Huanhuan Chen, Xin Yao. "Regularized Negative Correlation Learning for Neural Network Ensembles." IEEE Transactions on Neural Networks, 20(12):1962-1979, 2009. Available [here]


• Joseba Quevedo, Huanhuan Chen, Miquel A. Cuguero, Peter Tino, Vicenc Puig, D. Garcia, R. Sarrate and Xin Yao. "Combining Learning in Model Space Fault Diagnosis with Data Validation/Reconstruction: Application to the Barcelona Water Network." Engineering Applications of Artificial Intelligence , 30: 18-29, (2014). Available [here]


• Rodrigo G. F. Soares, Huanhuan Chen, Xin Yao. "Semisupervised Classification With Cluster Regularization." IEEE Transactions Neural Networks and Learning Systems , 23(11): 1779-1792 (2012). Available [here]
  Matlab software Availablehere


• Lean Yu, Huanhuan Chen, Shouyang Wang, Kin Keung Lai. "Evolving Least Squares Support Vector Machines for Stock Market Trend Mining." IEEE Transactions Evolutionary Computation, 13(1): 87-102 (2009). Available [here]


• Qi Guo, Tianshi Chen, Yunji Chen, Rui Wang, Huanhuan Chen, Weiwu Hu, Guoliang Chen. "Pre-Silicon Bug Forecast." IEEE Transactions on CAD of Integrated Circuits and Systems, 33(3): 451-463 (2014). Available [here]


• Alex Royal, P.R. Atkins, Michael Brennan, David Chapman, Huanhuan Chen, Anthony Cohn, K Foo, Kevin Goddard, Russell Hayes, Tong Hao, P. L. Lewin, Nicole Metje, Jen Muggleton, Adham Naji, Giovanni Orlando, Steve Pennock, Miles Redfern, Adrian Saul, Steve Swingler, Ping Wang and C.D.F. Rogers. "Site Assessment of Multiple Sensor Approaches for Buried Utility Detection." International Journal of Geophysics (IJGE'11), Volume 2011, Article ID 496123, 19 pages, (2011). http://dx.doi.org/10.1155/2011/496123 Available [here]

Book Chapter

• Huanhuan Chen, Anthony Cohn and Xin Yao. Ensemble Learning by Negative Correlation Learning.In Ensemble Learning: Theory and Application, Zhang Cha and Yunqian Ma (Ed.). DOI 10.1007/978-1-4419-9326-7_6, Springer-Verlag, 2012.


• Arjun Chandra, Huanhuan Chen and Xin Yao Trade-off between Diversity and Accuracy in Ensemble Generation. In Multi-objective Machine Learning, Yaochu Jin (Ed.), pp.429-464, DOI 10.1007/3-540-33019-4_19 Springer-Verlag, 2006.

Conference Papers

• Liangwei Chen, Xiren Zhou, Huanhuan Chen. "Audio Scanning Network：Bridging Time and Frequency Domains for Audio Classification". In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024.


• Xingyu Wu, Bingbing Jiang, Tianhao Wu, Huanhuan Chen. "Practical Markov Boundary Learning without Strong Assumptions". In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), 2023.


• Xin Wang, Shengfei Lyu, Xingyu Wu, Tianhao Wu, Huanhuan Chen. "Generalization Bounds for Estimating Causal Effects of Continuous Treatments". In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS'22), 2022.


• Tianhao Wu, Xingyu Wu, Xin Wang, Shikang Liu, and Huanhuan Chen. "Nonlinear Causal Discovery in Time Series". In Proceedings of 31st ACM International Conference on Information and Knowledge Management (CIKM'22), 2022.


• Xinyan Zhao, Feng Xiao, Haoming Zhong, Jun Yao, and Huanhuan Chen. "Condition Aware and Revise Transformer for Question Answering". In Proceedings of the World Wide Web Conference (WWW'20), 2020.


• Xingyu Wu, Bingbing Jiang, Yan Zhong, and Huanhuan Chen. "Tolerant Markov Boundary Discovery for Feature Selection". In Proceedings of the Conference on Information and Knowledge Management (CIKM'20), 2020.


• Xingyu Wu, Bingbing Jiang, Kui Yu, Huanhuan Chen, Chunyan Miao. "Multi-Label Causal Feature Selection". In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI'20), US, 2020.


• Yaqiang Yao, Jie Cao, and Huanhuan Chen. "Robust Task Grouping with Representative Tasks for Clustered Multi-Task Learning". In Proceedings of the ACM SIGKDD international conference on Knowledge Discovery and Data Mining (KDD'19), US, 2019.


• Bingbing Jiang, Xingyu Wu, Kui Yu, Huanhuan Chen. "Joint Semi-supervised Feature Selection and Classification through Bayesian Approach". In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI'19), US, 2019.


• Junyuan Hong, Huanhuan Chen, Feng Lin. "Disturbance Grassmann Kernels for Subspace-Based Learning". In Proceedings of the ACM SIGKDD international conference on Knowledge Discovery and Data Mining (KDD'18). , London, UK, August 19-23, 2018


• Yang Li, Junyuan Hong, Huanhuan Chen. "Sequential Data Classification in the Space of Liquid State Machines". In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'16), Riva del Garda, Italy, 2016


• Jiawei Liu, Zhenyu Liu, Huanhuan Chen. "Revisit Word Embeddings with Semantic Lexicons for Modeling Lexical Contrast". In Proceedings of International Conference on Big Knowledge (ICBK'17), Hefei, China, 2017


• Dandan Yang, Huanhuan Chen, Yinlong Song, Zhichen Gong. "Granger Causality for Multivariate Time Series Classification". In Proceedings of International Conference on Big Knowledge (ICBK'17), Hefei, China, 2017


• Zicheng Gong, Huanhuan Chen. "Model-Based Oversampling for Imbalanced Sequence Classification". In Proceedings of The 25th ACM International Conference on Information and Knowledge Management (CIKM'16), Indianapolis, USA, 2016


• Huanhuan Chen, FengZhen Tang, Peter Tino, Anthony G Cohn, Xin Yao. "Model Metric Co-learning for Time Series Classification" In Proceedings of the 25th International Joint Conferences on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015


• Fengzhen Tang, Peter Tiño, Huanhuan Chen."Learning the deterministically constructed Echo State Networks." In Proeedings of the 2014 International Joint Conference on Neural Networks (IJCNN'14),2014: 77-83


• Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, Huanhuan Chen."Support Vector Ordinal Regression using Privileged Information." ESANN 2014


• Huanhuan Chen, Fengzhen Tang, Peter Tino, Xin Yao. "Model-based kernel for efficient time series analysis." In Proceedings of the 19th ACM SIGKDD international conference on Knowledge Discovery and Data Mining (KDD'13). Chicago, USA, August 11-14, 2013. Available [here]


• Huanhuan Chen, Anthony G. Cohn. "Buried Utility Pipeline Mapping Based on Multiple Spatial Data Sources: A Bayesian Data Fusion Approach." In Proceedings of the 22nd International Joint Conferences on Artificial Intelligence (IJCAI'11), Barcelona, Spain, 2011. Available [here]. Oral presentation and Poster presentation.


• Huanhuan Chen, Anthony G. Cohn: Buried Utility Pipeline Mapping based on Street Survey and Ground Penetrating Radar. In Proceedings of the 19th European Conference on Artificial Intelligence (ECAI'10) 2010:987-988, Lisbon, Portugal, 2010. Available [here]


• Huanhuan Chen, and Anthony G. Cohn. "Probabilistic conic mixture model and its applications to mining spatial ground penetrating radar data." In Workshop in SIAM Conference on Data Mining (WSDM'10), Columbus, 2010. Available [here]


• Huanhuan Chen, Anthony G. Cohn. "Probabilistic robust hyperbola mixture model for interpreting ground penetrating radar data." In Proceedings of the 2010 IEEE World Congress on Computational intelligence (WCCI'10), Barcelona, 2010. Available [here]


• Shuo Wang, Huanhuan Chen, Xin Yao. "Negative correlation learning for classification ensembles." In Proeedings of the 2010 International Joint Conference on Neural Networks (IJCNN,10), Barcelona, 2010. Available [here]


• Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao. "Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning." In Proceedings of the 19th International Conference on Artificial Neural Networks (ICANN'09), Cyprus, 2009. Available [here]


• Huanhuan Chen, Xin Yao. "Evolutionary random neural ensembles based on negative correlation learning." In Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC'07), Singapore, 2007. Available [here]


• Huanhuan Chen, Peter Tiño, Xin Yao. "A Probabilistic Ensemble Pruning Algorithm." In Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (WICDM'06), Hong Kong, 2006. Available [here]

PhD Dissertation

• Huanhuan Chen : Diversity and Regularization in Neural Network Ensembles. School of Computer Science, University of Birmingham.
  (2011 IEEE Computational Intelligence Society Outstanding PhD Dissertation Award. )
  (British Computer Society Distinguished Dissertations Award (the Runner up)).