吕 宝粮 教授
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办公室电话：+86-21-3420-5422
办公地点：SEIEE-3-431
电子邮件：blu@cs.sjtu.edu.cn
实验室： 智能计算与智能系统重点实验室、 上海市教委智能交互与认知工程重点实验室


研究兴趣
教育背景
工作经验
教授课程
论文发表
项目资助
获奖信息
学术服务


仿脑计算理论与模型、神经网络、机器学习、脑-机交互、情感计算
1991/04-1994/03, 日本京都大学， 电气工程系， 工学博士
1986/09-1989/03, 西北工业大学， 计算机科学与技术系， 工学硕士
1978/02-1982/01, 山东化工学院，化工自动化及仪表专业，工学学士

2002/08至今，上海交通大学计算机科学与工程系， 教授、博士生导师
1999/04-2002/08，日本理化学研究所脑科学综合研究中心，研究员
1994/04-1999/03，日本理化学研究所仿生物控制研究中心，研究员
1989/04-1991/03，青岛化工学院自动化系，助教
1982/02-1986/08，青岛化工学院自动化系，助教


神经网络理论及其应用
超并行机器学习与海量数据挖掘



2020
1. Wei-Long Zheng, Kunpeng Gao, Gang Li, Wei Liu, Chao Liu, Jing-Quan Liu, GuoxingWang, Bao-Liang Lu: VigilanceEstimation Using a Wearable EOG Device in Real Driving Environment. IEEE Trans. Intelligent TransportationSystems 21(1): 170-184 (2020)
2. Dongrui Wu, Yifan Xu, Bao-Liang Lu: Transfer Learning forEEG-Based Brain-Computer Interfaces: A Review of Progresses Since 2016. CoRRabs/2004.06286 (2020)
3. Xun Wu, Wei-Long Zheng, Bao-Liang Lu: Investigating EEG-Based Functional Connectivity Patterns forMultimodal Emotion Recognition. CoRRabs/2004.01973 (2020)
4. Yu-Ting Lian, Wei Liu, Bao-Liang Lu, MultimodalEmotion Recognition Using Deep Generalized Canonical Correlation Analysis withan Attention Mechanism, to appear in IJCNN2020
5. Le-Yan Tao, Bao-Liang Lu, Emotion Recognition underSleep Deprivation Usinga Multimodal Residual LSTM Network, to appear in IJCNN 2020
6. Wenrui Mu, Bao-Liang Lu, Examining FourExperimental Paradigms for EEG-Based Sleep Quality Evaluation with DomainAdaptation, to appear in EMBC 2020

2019

1. Wei-Long Zheng, Wei Liu, Yifei Lu, Bao-Liang Lu, andAndrzej Cichocki, EmotionMeter: A Multimodal Framework for Recognizing HumanEmotions. IEEE Transactions on Cybernetics, 49(3):1110-1122, 2019
2. Yun Luo, Li-Zhen Zhu, Bao-Liang Lu, A GAN-Based DataAugmentation Method for Multimodal Emotion Recognition. ISNN (1) 2019: 141-150
3. Xun Wu, Wei-Long Zheng, Bao-Liang Lu, Identifying FunctionalBrain Connectivity Patterns for EEG-Based Emotion Recognition. IEEE NER 2019:235-238
4. Tian-Hao Li, Wei Liu, Wei-Long Zheng, Bao-Liang Lu,Classification of Five Emotions from EEG and Eye Movement Signals:Discrimination Ability and Stability over Time. IEEE NER 2019: 607-610
5. Li-Ming Zhao, Rui Li, Wei-Long Zheng, Bao-Liang Lu,Classification of Five Emotions from EEG and Eye Movement Signals:Complementary Representation Properties. IEEE NER 2019: 611-614
6. Bo-Qun Ma, He Li, Yun Luo, Bao-Liang Lu, DepersonalizedCross-Subject Vigilance Estimation with Adversarial Domain Generalization,Proc. IJCNN 2019, Budabest
7. Lan-Qing Bao, Jie-Lin Qiu, Hao Tang, Wei-Long Zheng, Bao-LiangLu, Investigating Sex Differences in Classification of Five Emotions fromEEG and Eye Movement Signals, Proc. IEEE EMBC 2019, Berlin
8. Jiang-Jian Guo, Rong Zhou, Li-Ming Zhao, Bao-Liang Lu,Multimodal Emotion Recognition from Eye Image, Eye Movement and EEG Using DeepNeural Networks, Proc. IEEE EMBC 2019, Berlin
9. Jiaxin Ma, Hao Tang, Wei-Long Zheng, Bao-Liang Lu,Emotion Recognition using Multimodal Residual LSTM Network, to appear in Proc.ACM Multimedia 2019.
10. Shu Jiang, Zhuosheng Zhang, Hai Zhao, Jiangtong Li, YangYang, Bao-Liang Lu, Ning Xia, Judging Chemical Reaction PracticalityFrom Positive Sample only Learning. CoRR abs/1904.09824, 2019



2018
1. Wei-Long Zheng, Wei Liu, Yifei Lu, Bao-Liang Lu*, and Andrzej Cichocki, EmotionMeter: A Multimodal Framework for Recognizing Human Emotions. IEEE Transactions on Cybernetics, 2018
2. Rui Wang, Hai Zhao, Sabine Ploux, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita: Graph-Based Bilingual Word Embedding for Statistical Machine Translation. ACM Trans. Asian & Low-Resource Lang. Inf. Process. 17(4): 31:1-31:23, 2018
3. Yun Luo, Bao-Liang Lu*, EEG Data Augmentation for Emotion Recognition Using a Conditional Wasserstein GAN, Proc. IEEE EMBC2018
4. Yimin Yang, Q. M. Jonathan Wu, Wei-Long Zheng, Bao-Liang Lu: EEG-Based Emotion Recognition Using Hierarchical Network With Subnetwork Nodes. IEEE Trans. Cognitive and Developmental Systems 10(2): 408-419 (2018)
5. Jie-Lin Qiu, Wei Liu, Bao-Liang Lu*: Multi-view Emotion Recognition Using Deep Canonical Correlation Analysis. ICONIP (5) 2018: 221-231
6. Yun Luo, Si-Yang Zhang, Wei-Long Zheng, Bao-Liang Lu*: WGAN Domain Adaptation for EEG-Based Emotion Recognition. ICONIP (5) 2018: 275-286
7. Li-Ming Zhao, Xin-Wei Li, Wei-Long Zheng, Bao-Liang Lu*: Active Feedback Framework with Scan-Path Clustering for Deep Affective Models. ICONIP (2) 2018: 330-340
8. He Li, Yi-Ming Jin, Wei-Long Zheng, Bao-Liang Lu*: Cross-Subject Emotion Recognition Using Deep Adaptation Networks. ICONIP (5) 2018: 403-413
9. Yini Deng, Yingying Jiao, Bao-Liang Lu: Driver Sleepiness Detection Using LSTM Neural Network. ICONIP (4) 2018: 622-633
10. He Li, Wei-Long Zheng, Bao-Liang Lu*: Multimodal Vigilance Estimation with Adversarial Domain Adaptation Networks. IJCNN 2018: 1-6
11. Jia-Jun Tong, Yun Luo, Bo-Qun Ma, Wei-Long Zheng, Bao-Liang Lu*, Xiao-Qi Song, Shi-Wei Ma: Sleep Quality Estimation with Adversarial Domain Adaptation: From Laboratory to Real Scenario. IJCNN 2018: 1-8
12. Changde Du, Changying Du, Hao Wang, Jinpeng Li, Wei-Long Zheng, Bao-Liang Lu*, Huiguang He: Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data. ACM Multimedia 2018: 108-116
13. Changde Du, Changying Du, Hao Wang, Jinpeng Li, Wei-Long Zheng, Bao-Liang Lu, Huiguang He: Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data. CoRR abs/1808.02096 (2018)
14. Tian-Hao Li, Wei Liu, Wei-Long Zheng, Bao-Liang Lu：Classification of Five Emotions from EEG and Eye Movement Signals: Discrimination Ability and Stability over Time, to appear in IEEE NER’2019
15. LiMing Zhao, Rui Li, Wei-Long Zheng, Bao-Liang Lu*: Classification of Five Emotions from EEG and Eye Movement Signals: Complementary Representation Properties, to appear in IEEE NER’2019
16. Xun Wu, Wei-Long Zheng, Bao-Liang Lu*: Identifying Functional Brain Connectivity Patterns for EEG-Based Emotion Recognition, to appear in IEEE NER’2019

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2017

1. Wei-Long Zheng, and Bao-Liang Lu, Identifying Stable Patterns over Time for Emotion Recognition from EEG, IEEE Transactions on Affective Computing， 2017
2. Wei-Long Zheng and Bao-Liang Lu, A multimodal approach to estimating vigilance using EEG and forehead EOG. Journal of Neural Engineering, 14(2): 026017, 2017
3. Yong Peng, Bao-Liang Lu:Discriminative extreme learning machine with supervised sparsity preserving for imageClassification, Neurocomputing, 261: 242-252,2017
4. Yong Peng, Bao-Liang Lu:Robust structured sparse representation via half-quadratic optimization for face recognition. Multimedia Tools Appl. 76(6): 8859-8880,2017
5. Kai-Ming Jiang, Ya-Jing Chen, Jin-Xiong Lv, Bao-Liang Lu, Lei Xu: Bootstrapping integrative hypothesis test for identifying biomarkers that differentiates lung cancer and chronic obstructive pulmonary disease. Neurocomputing, 269: 40-46,2017
6. Si-Yuan Wu, Moritz Schaefer, Wei-Long Zheng, Bao-Liang Lu, Neural Patterns between Chinese and Germans for EEG-based Emotion Recognition, Proc. of the 8th International IEEE EMBS Conference on Neural Engineering, Shanghai, 2017.
7. Zhen-Feng Shi, Chang Zhou, Wei-Long Zheng and Bao-Liang Lu, Attention Evaluation with Eye Tracking Glasses for EEG-based Emotion Recognition, Proc. of the 8th International IEEE EMBS Conference on Neural Engineering, Shanghai, 2017.
8. Li-Huan Du, Wei Liu, Wei-Long Zheng and Bao-Liang Lu, Detecting Driving Fatigue with Multimodal Deep Learning, Proc. of the 8th International IEEE EMBS Conference on Neural Engineering, Shanghai, 2017.
9. Yingying Jiao and Bao-Liang Lu. An Alpha Wave Pattern from Attenuation to Disappearance for Predicting the Entry into Sleep during Simulated Driving, Proc. of the 8th International IEEE EMBS Conference on Neural Engineering, Shanghai, 2017
10. Hao Tang, Wei Liu, Wei-Long Zheng, and Bao-Liang Lu, Multimodal Emotion Recognition Using Deep Neural Networks, Proc. ICONIP2017, Guangzhou, 2017.
11. Xue Yan, Wei-Long Zheng, Wei Liu, and Bao-Liang Lu, Identifying Gender Differences in Multimodal Emotion Recognition Using Bimodal Deep AutoEncoder, Proc. ICONIP2017, Guangzhou, 2017.
12. Xue Yan, Wei-Long Zheng, Wei Liu, and Bao-Liang Lu, Investigating Gender Differences of Brain Areas in Emotion Recognition Using LSTM Neural Network, Proc. ICONIP2017, Guangzhou, 2017.
13. Xing-Zan Zhang, Wei-Long Zheng, and Bao-Liang Lu, EEG-Based Sleep Quality Evaluation with Deep Transfer Learning, Proc. ICONIP2017, Guangzhou, 2017.
14. Wei-Ye Zhao, Sheng Fang, Ting Ji, Qian Ji, Wei-Long Zheng, and Bao-Liang Lu, Emotion Annotation using Hierarchical Aligned Cluster Analysis, Proc. ICONIP2017, Guangzhou, 2017.
15. Yi-Ming Jin, Yu-Dong Luo, Wei-Long Zheng, Bao-Liang Lu, EEG-based Emotion Recognition Using Domain Adaptation Network, Proc. ICOT2017, Singapore, 2017
16. Yingying Jiao and Bao-Liang Lu, Detecting Driver Sleepiness from EEG Alpha Wave during Daytime Driving, Proc. IEEE BIBM2017,Kansas City, USA, 2017

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2016

1. Wei-Long Zheng and Bao-Liang Lu*, Personalizing EEG-based Affective Models with Transfer Learning, Proc. of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York
2. Rui Wang, Hai Zhao*, Sabine Ploux*, Bao-Liang Lu and Masao Utiyama, A Bilingual Graph-based Semantic Model for Statistical Machine Translation, Proc. of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York
3. Xue-Qin Huo, Wei-Long Zheng, Bao-Liang Lu*, Driving Fatigue Detection with Fusion of EEG and Forehead EOG, Proc. of 2016 International Joint Conference on Neural Networks (IJCNN-16)
4. Li-Li Wang, Wei-Long Zheng, Hai-Wei Ma, and Bao-Liang Lu*, Measuring Sleep Quality from EEG with Machine Learning Approaches, Proc. of 2016 International Joint Conference on Neural Networks (IJCNN-16)
5. Jincheng Mei, Hao Zhang, Bao-Liang Lu*: On the Reducibility of Submodular Functions, Proc. of The 19th International Conference on Artificial Intelligence and Statistics, May 9 - 11, 2016, Cadiz, Spain
6. Wei-Long Zheng, Shan-Chun Shen, Bao-Liang Lu*, Online Depth Image-Based Object Tracking with Sparse Representation and Object Detection, Neural Process Letter
7. Yong Peng, Wei-Long Zheng, Bao-Liang Lu*, An unsupervised discriminative extreme learning machine and its applications to data clustering. Neurocomputing 174: 250-264 (2016)
8. Yong Peng, Bao-Liang Lu*, Discriminative manifold extreme learning machine and applications to image and EEG signal classification. Neurocomputing 174: 265-277 (2016)
9. Jincheng Mei, Hao Zhang, Bao-Liang Lu*, On the Reducibility of Submodular Functions. CoRR abs/1601.00393 (2016)
10. Wei-Long Zheng, Jia-Yi Zhu, Bao-Liang Lu*, Identifying Stable Patterns over Time for Emotion Recognition from EEG. CoRR abs/1601.02197 (2016)
11. Wei Liu, Wei-Long Zheng, Bao-Liang Lu*, Multimodal Emotion Recognition Using Multimodal Deep Learning. CoRR abs/1602.08225 (2016)
12. Yingying Jiao, Bao-Liang Lu*, Detecting slow eye movement for recognizing driver’s sleep onset period with EEG features, Proc. of IEEE EMBC2016
13. Wei Liu, Wei-Long Zheng, Bao-Liang Lu*, Emotion recognition using multimodal deep learning, Proc. of ICONIP2016, Kyoto, 2016
14. Nan Zhang, Wei-Long Zheng, Wei Liu, Bao-Liang Lu*, Continuous vigilance estimation using LSTM neural networks, Proc. of ICONIP2016, Kyoto, 2016
15. Rui Wang, Masao Utiyama, Isao Goto, Eiichiro Sumita, Hai Zhao,Bao-Liang Lu: Converting Continuous-Space Language Models into N-gram Language Models with Efficient Bilingual Pruning for Statistical Machine Translation. ACM Trans. Asian & Low-Resource Lang. Inf. Process. 15(3):11:1-11:26
16. Rui Wang, Hai Zhao, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita: Connecting Phrase based Statistical Machine Translation Adaptation. Proc. of COLING 2016: 3135-3145
17. Rui Wang, Hai Zhao, Sabine Ploux,Bao-Liang Lu, Masao Utiyama: A Novel Bilingual Word Embedding Method for Lexical Translation Using Bilingual Sense Clique. CoRR abs/1607.08692 (2016)
18. Wei Liu, Wei-Long Zheng,Bao-Liang Lu: Multimodal Emotion Recognition Using Multimodal Deep Learning. CoRR abs/1602.08225 (2016)
19. Rui Wang, Hai Zhao, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita: Connecting Phrase based Statistical Machine Translation Adaptation. CoRR abs/1607.08693 (2016)
20. Wei-Long Zheng, Jia-Yi Zhu, Bao-Liang Lu: Identifying Stable Patterns over Time for Emotion Recognition from EEG. CoRR abs/1601.02197 (2016)

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2015

1. Mu Li, Wei Bi, James T. Kwok, and Bao-Liang Lu, Large-Scale Nystrom Kernel Matrix Approximation Using Randomized SVD. IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 1, pp. 152-164, 2015
2. Yong Peng, Bao-Liang Lu, and Suhang Wang, Enhanced Low-rank Representation via Sparse Manifold Adaption for Semi-supervised Learning, Neural Networks vol. 65, pp. 1-17, 2015
3. Yong Peng and Bao-Liang Lu, Hybrid Learning Clonal Selection Algorithm, Information Sciences, vol. 296, pp. 128-146, 2015
4. Yong Peng, Suhang Wang, Xianzhong Long, and Bao-Liang Lu, Discriminative Graph Regularized Extreme Learning Machine and Its Application to Face Recognition, Neurocomputing, vol. 149, pp.340-353, 2015
5. Rui Wang, Masao Utiyama, Isao Goto, Eiichiro Sumita, Hai Zhao and Bao-Liang Lu. Converting Continuous-Space Language Models into N-gram Language Models with Efficient Bilingual Pruning for Statistical Machine, to appear in ACM Transactions on Asian Low-Resourse Languange Information Process.
6. Jincheng Mei, Kang Zhao, Bao-Liang Lu, On Unconstrained Quasi-Submodular Function Optimization, The 29th AAAI Conference on Artificial Intelligence (AAAI2015): 1191-1197
7. Yangcheng He, Hongtao Lu, Bao-Liang Lu, Graph regularized non-negative local coordinate factorization with pairwise constraints for image representation. Proc. of the 2015 IEEE International Conference on Multimedia and Expo (ICME 2015)
8. Li Wu, Kang Zhao, Hongtao Lu, Zhen Wei, Bao-Liang Lu, Distance Preserving Marginal Hashing for image retrieval. Proc. of the 2015 IEEE International Conference on Multimedia and Expo (ICME 2015)
9. Wei-Long Zheng, Hao-Tian Guo, and Bao-Liang Lu, Revealing Critical Channels and Frequency Bands for EEG-based Emotion Recognition with Deep Belief Network, to appear in Proc. of the 7th International IEEE EMBS Conference on Neural Engineering (IEEE EMBS2015)
10. Xiang-Yu Gao, Yu-Fei Zhang, Wei-Long Zheng, and Bao-Liang Lu, Evaluation Driving Fatigue Detection Algorithms Using Eye Tracking Glasses, to appear in Proc. of the 7th International IEEE EMBS Conference on Neural Engineering (IEEE EMBS2015)
11. Yu-Fei Zhang, Xiang-Yu Gao, Jia-Yi Zhu, Wei-Long Zheng, and Bao-Liang Lu, A Novel Approach to Driving Fatigue Detection Using Forehead EOG, to appear in Proc. of the 7th International IEEE EMBS Conference on Neural Engineering (IEEE EMBS2015)
12. Yong Peng and Bao-Liang Lu, Robust Group Sparse Representation via hafl-quadratic Optimization for Face Recognition, to appear in Proc. of Canadian Conference on Electrical and Computier Engineering (CCECE2015)
13. Wei-Long Zheng, Roberto Santana, and Bao-Liang Lu, Comparison of Classification Methods for EEG-based Emotion Recognition, to appear in Proc. of the 2015 World Congress on Medical Physics and Biomedical Engineering
14. Jia-Yi Zhu, Wei-Long Zheng, and Bao-Liang Lu, Cross-subject and Cross-gender Emotion Classification from EEG, to appear in Proc. of the 2015 World Congress on Medical Physics and Biomedical Engineering
15. Rui Wang, Hai Zhao, Bao-Liang Lu, Massao Utiyama and Eiichiro Sumita, Bilingual Continuous-Space Language Model, to appear in IEEE/ACM Transactions on Audio, Speech, and Language Processing
16. Wei-Long Zheng, Bao-Liang Lu, Investigating Critical Frequency Bands and Channels for EEG-based Emotion Recognition with Deep Neural Networks, to appear in IEEE Transactions on Autonomous Mental Development
17. Yi-Fei Lu, Wei-Long Zheng, Bin-Bin Li, Bao-Liang Lu, Combining Eye Movements and EEG to Enhance Emotion Recognition, to appear in Proc. of the International Joint Conference on Artificial Intelligence (IJCAI2015)
18. Rui Wang , Hai Zhao and Bao-Liang Lu, English to Chinese Translation: How Chinese Character Matters? to appear in Proc. of the 29th Pacific Asia Conference on Language, Information and Computation
19. Yang Cao and Bao-Liang Lu, Intensity-Depth Face Alignment Using Cascade Shape Regression, to appear in Proc. of the 22nd International Conference on Neural Information Processing (ICONIP2015)
20. Yong-Qi Zhang, Wei-Long Zheng, and Bao-Liang Lu, Transfer Components Between Subjects for EGG-based Driving Fatigue Detection, to appear in Proc. of the 22nd International Conference on Neural Information Processing (ICONIP2015)
21. Wei-Long Zheng, Yong-Qi Zhang, Jia-Yi Zhu, and Bao-Liang Lu, Transfer Components between Subjects for EEG-based Emotion Recognition, to appear in Proc. of the 6th International Conference on Affective Computing and Intelligent Interaction (ACII2015)

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2014

1. Xiaolin Wang, Hai Zhao and Bao-Liang Lu, A Meta-Top-Down Method for Large-Scale Hierarchical Classification, IEEE Transactions on Knowledge and Data Engineering, vol. 26, pp. 500-513, 2014
2. Xiao-Wei Wang, Dan Nie, and Bao-Liang Lu, Emotional State Classification from EEG Data Using Machine Learning Approach, Neurocomputing, vol. 129, pp. 94-106, 2014
3. Xiaolin Wang, Yangyang Chen, Hai Zhao, Bao-Liang Lu, Parallelized Extreme Learning Machine Ensemble Based on Min-max Modular Network, Neurocomputing, vol. 128, pp. 31-41, 2014
4. Wei-Long Zheng, Jia-Yi Zhu, Yong Peng, Bao-Liang Lu, EEG-Based Emotion Classification Using Deep Belief Networks, IEEE International Conference on Multimedia and Expo (IEEE ICME2014)
5. Wei-Long Zheng, Bo-Nan Dong, and Bao-Liang Lu, Multimodal Emotion Recognition Using EEG and Eye Tracking Data, International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC2014)
6. Yong Peng, Jia-Yi Zhu, Wei-Long Zheng, Bao-Liang Lu, EEG-Based Emotion Recognition with Manifold Regularized Extreme Learning Machine, International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC2014)
7. Xuemin Zhu, Wei-Long Zheng, Bao-Liang Lu, Xiaoping Chen, Shanguang Chen and Chunhui Wang, EOG-Based Drowsiness Detection Using Convolutional Neural Networks, International Joint Conference on Neural Networks (IJCNN). 2014: 128-134
8. Jia-Yi Zhu, Wei-Long Zheng, Ruo-Nan Duan, Yong Peng and Bao-Liang Lu, EGG-Based Emotion Recognition Using Discriminative Graph Regularized Extreme Learning Machine, International Joint Conference on Neural Networks (IJCNN). 2014: 525-532
9. Ying-Ying Jiao, Yong Peng, and Bao-Liang Lu, Recognizing Slow Ey Movement for Driver Fatigue Detection with Machine Learning Approach, International Joint Conference on Neural Networks (IJCNN). 2014: 4035-4041
10. Wei-Long Zheng, Jia-Yi Zhu, and Bao-Liang Lu, Multimodal Emotion Analysis in Response to Multimedia, Proc. of IEEE International Conference on Multimedia and Expo (IEEE ICME2014)
11. Rui Wang, Hai Zhao, Bao-Liang Lu, Masao Utiyama and Eiichro Sumita, Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation, Proc. of the 2014 Conference on Empirical Methods on Natural Language Processing (EMNLP2014)
12. Yong Peng, Bao-Liang Lu, Discriminative Manifold Extreme Learning Machine and Applications to Image and EEG Signal Classificatin, International Conference on Extreme Learning Machines (ELM2014)
13. Yong Peng, Bao-Liang Lu, An Unsupervised Discriminative Extreme Learning Machine, International Conference on Extreme Learning Machines (ELM2014)
14. Shan-Chun Shen, Wei-Long Zheng and Bao-Liang Lu, Onlin Object Tracking Based on Depth Image with Sparse Coding, Proc. of the 21st International Conference of Neural Information Processing (ICONIP2014)
15. Jincheng Mei and Bao-Liang Lu, Saliency Level Set Evolution, Proc. of the 21st International Conference of Neural Information Processing (ICONIP2014)
16. Jing-Nan Gu, Hong-Tao Lu, Bao-Liang Lu, An Integrated Gaussian Mixture Model to Estimate Vigilance Level Based on EEG Recordings, Neurocomputing vol. 129, pp. 107-113, 2014

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2013

1. Li-Chen Shi and Bao-Liang Lu, EEG-based vigilance estimation using extreme learning machines. Neurocomputing, vol. 102, pp. 135-143, 2013
2. Hai Zhao, Masao Utiyama, Eiichiro Sumita, Bao-Liang Lu, An Empirical Study on Word Segmentation for Chinese Machine Translation. Proc. of 14th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing2013), pp. 248-263, 2013
3. Yong Peng and Bao-Liang Lu, A Hierarchical Particle Swarm Optimizer with Latin Sampling Based Memetic Algorithm for Numerical Optimization. Applied Soft Computing, vol. 13, no. 5, pp. 2823-2836, 2013
4. Yong Peng, Suhang Wang, Xianzhong Long and Bao-Liang Lu, Discriminative Graph Regularized Extreme Learning Machine and Its application to Face Recognition. Neurocomputing
5. Li-Chen Shi, Ruo-Nan Duan and Bao-Liang Lu, A Robust Principal Component Analysis Algorithm for EEG-Based Vigilance Estimation, Proc. of International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6623-6626, 2013
6. Li-Chen Shi, Ruo-Nan Duan and Bao-Liang Lu, Differential Entropy Feature for EEG-based Vigilance Estimation, Proc. of International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6627-6630, 2013
7. Ruo-Nan Duan, Jia-Yi Zhu and Bao-Liang Lu, Differential Entropy Feature for EEG-based Emotion Classification, Proc. of the 6th International IEEE EMBS Conference on Neural Engineering (NER2013)
8. Yong Peng, Suhang Wang, Shen Wang, and Bao-Liang Lu, Structure Preserving Low-rank Representation for Semi-supervised Face Recognition, Proc. of the 20th International Conference of Neural Information Processing (ICONIP2013)
9. Yong Peng, Suhang Wang and Bao-Liang Lu, Marginalized Denoising Autoencoder via Graph Regularization for Domain Adaptation, Proc. of the 20th International Conference of Neural Information Processing (ICONIP2013)
10. Yang Cao and Bao-Liang Lu, Real-time Head Detection with Kinect for Driving Fatigue Detection, Proc. of the 20th International Conference of Neural Information Processing (ICONIP2013)
11. Fan Li, Xiao-Wei Wang and Bao-Liang Lu, Detection of Driving Fatigue Based on Grip Force on Steering Wheel with Wavelet Transformation and Support Vector Machine, Proc. of the 20th International Conference of Neural Information Processing (ICONIP2013)
12. Xiao-Lin Wang, Hai Zhao and Bao-Liang Lu, Labeled Alignment for Recognizing Textual Entailment, Proc. of The 6th International Joint Conference on Natural Language Processing (IJCNLP2013)
13. Rui Wang, Masao Utiyama, Isao Goto, Eiichro Sumita, Hai Zhao and Bao-Liang Lu, Converting Continuous-Space Language Models into N-gram Language Models for Statistical Machine Translation, Proc. of the 2013 Conference on Empirical Methods on Natural Language Processing (EMNLP2013)
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2012

1. Bing Li, Xiao-Chen Lian, Bao-Liang Lu: Gender classification by combining clothing, hair and facial component classifiers. Neurocomputing 76(1): 18-27 (2012)
2. Tian-Xiang Wu, Xiao-Chen Lian, Bao-Liang Lu: Multi-view gender classification using symmetry of facial images. Neural Computing and Applications 21(4): 661-669 (2012)
3. Ruo-Fei Du, Ren-Jie Liu, Tian-Xiang Wu, Bao-Liang Lu: Online Vigilance Analysis Combining Video and Electrooculography Features. ICONIP (5) 2012: 447-454
4. Ruo-Nan Duan, Xiao-Wei Wang, Bao-Liang Lu: EEG-Based Emotion Recognition in Listening Music by Using Support Vector Machine and Linear Dynamic System. ICONIP (4) 2012: 468-475
5. Hui Sun, Bao-Liang Lu: EEG-Based Fatigue Classification by Using Parallel Hidden Markov Model and Pattern Classifier Combination. ICONIP (4) 2012: 484-491
6. Shaohua Yang, Hai Zhao and Bao-Liang Lu. A Machine Translation Approach for Chinese Whole-Sentence Pinyin-to-Character Conversion, PACLIC-26, Bali, Indonesia, November, 2012
7. Yangyang Chen, Bao-Liang Lu, Hai Zhao: Parallel learning of large-scale multi-label classification problems with min-max modular LIBLINEAR. IJCNN 2012: 1-7
8. Zheng-Ping Wei, Bao-Liang Lu: Online vigilance analysis based on electrooculography. IJCNN 2012: 1-7
9. Yong Peng, Bao-Liang Lu: Immune clonal algorithm based feature selection for epileptic EEG signal classification. ISSPA 2012: 848-853
10. Shaohua Yang, Hai Zhao, Xiaolin Wang and Bao-liang Lu, Spell Checking for Chinese, Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12), pages 730-736, Istanbul, Turkey, May, 2012
11. Chun-Fang Gao, Bao-Liang Lu and Jia-Xin Ma, A New Method of Extracting Vigilant Feature from Electrooculography by Using Wavelet Packet Transform, Chinese Journal of Biomedical Engineering, vol. 31, no. 5, pp. 641-648 (2012)
12. Dan Nie, Xiao-Wei Wang, Ruo-Nan Duan and Bao-Liang Lu, A Survey on EEG based Emotion Recognition, Chinese Journal of Biomedical Engineering, vol. 31, no. 4, pp. 595-606 (2012)
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2011

1. Bing Li, Rong Xiao, Zhiwei Li, Rui Cai, Bao-Liang Lu, and Lei Zhang, Rank-SIFT: Learning to Rank Repeatable Local Interest Points, Proc. of 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 20-25, 2011.
2. Mu Li, Xiao-Chen Lian, James T. Kwok, and Bao-Liang Lu, Time and Space Efficient Spectral Clustering via Column Sampling, Proc. of 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 20-25, 2011.
3. Dan Nie, Xiao-Wei Wang, Li-Chen Shi, and Bao-Liang Lu, EEG-based Emotion Recognition during Watching Movies, Proc. of 5th International IEEE EMBC Conference on Neural Engineering (NER), pp. 667-670, Cancun, Mexico, April 27-May 1, 2011.
4. Wen-Yun Yang , Bao-Liang Lu, James T. Kwok, Incorporating Cellular Sorting Structure for Better Prediction of Protein Subcellular Locations. Journal of Experimental and Theoretical Artificial Intelligence (JETAI)，vol. 23, pp. 79-95, 2011.
5. Zheng Ji and Bao-Liang Lu: "A Support Vector Machine Classifier with Automatic Confidence and Its Application to Gender Classification", Neuraocomputing, vol. 74, pp. 1926-1935, 2011.
6. Bao-Liang Lu, Xiao-Lin Wang, Yang Yang, and Hai Zhao: "Learning from Imbalanced Data Sets with a Min-max Modular Support Vector Machine ", Frontiers of Electrical and Electronic Engineering in China, vol. 6, no. 1, pp. 56-71, 2011.
7. L. C. Shi, Y. Li, R. H. Sun,B. L. Lu, "A sparse common spatial pattern algorithm for brain-computer interface", 18th International Conference on Neural Information Processing (ICONIP 2011).
8. X. W. Wang, D. Nie, B. L. Lu, "EEG-based emotion recognition using frequency domain features and support vector machines", 18th International Conference on Neural Information Processing (ICONIP 2011).
9. J. Wu, L. C. Shi, B. L. Lu, "Removing unrelated features based on linear dynamical system for motor-imagery-based brain-computer interface", 18th International Conference on Neural Information Processing (ICONIP 2011).
10. Zhong-Lei Gu, Li-Chen Shi, Bao-Liang Lu, "Evidence of Rapid Gender Processing Revealed by ERSP", 33rd Annual International Conference of the IEEE EMBS.
11. Hao-Yu Cai, Jia-Xin Ma, Li-Chen Shi, Bao-Liang Lu, "A Novel Method for EOG Features Extraction from the Forehead", 33rd Annual International Conference of the IEEE EMBS.
12. Xiao-lin Wang, Hai Zhao, Bao-Liang Lu, "Redundancy Removal to Selectively Diversify Information Retrieval Results", The 9th NTCIR Workshop Meeting. Evaluation of Information Access Technologies: Information Retrieval.
13. Xiao-lin Wang, Hai Zhao, Bao-Liang Lu,"GeoTime Retrieval through Passage-based Learning to Rank", The 9th NTCIR Workshop Meeting. Evaluation of Information Access Technologies: Information Retrieval.
14. Xiao-lin Wang, Hai Zhao, Bao-Liang Lu, "Enhance Top-down method with Meta-Classification for Very Large-scale Hierarchical Classification", IJCNLP2011 The 5th International Joint Conference on Natural Language Processing.
15. Bao-Liang Lu, Liqing Zhang, James T. Kwok: Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part I Springer 2011.
16. Bao-Liang Lu, Liqing Zhang, James T. Kwok: Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part II Springer 2011.
17. Bao-Liang Lu, Liqing Zhang, James T. Kwok: Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part III Springer 2011.
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2010

1. Yan-Ming Tang and Bao-Liang Lu, Age Classification Combining Contour and Texture Feature, Proceedings of 17th International Conference on Neural Information Processing (ICONIP2010), Sydney, Australia, November 22-25, 2010.
2. Tian-Xiang Wu and Bao-Liang Lu, Multi-view Gender Classification Using Hierarchical Classifiers Structure, Proceedings of 17th International Conference on Neural Information Processing (ICONIP2010), Sydney, Australia, November 22-25, 2010.
3. Qi Kng, Bao-Liang Lu, Adaptive Ensemble Learning Strategy Using an Assistant Classifier for Large-scale Imbalanced Patent, to appear in Proceedings of 17th International Conference on Neural Information Processing (ICONIP2010), Sydney, Australia, November 22-25, 2010.
4. Xuezhe Ma, Xiaotian Zhang, Hai Zhao and Bao-Liang Lu, Dependency Parser for Chinese Constituent Parsing, CIPS-SIGHAN-2010, August, 2010, Beijing, China.
5. Jia-Xin Ma, Li-Chen Shi and Bao-Liang Lu, Vigilance Estimation by Using Electrooculographic Features, Proceedings of 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), pp. 6591-6594, Buenos Aires, Argentina, August 31- September 4, 2010.
6. Li-Chen Shi, Bao-Liang Lu: Off-Line and On-Line Vigilance Estimation Based on Linear Dynamical System and Manifold Learning, Proc. of 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), pp. 6587-6590, Buenos Aires, Argentina, August 31- September 4, 2010.
7. Georg Bartels, Li-Chen Shi, Bao-Liang Lu: Automatic Artifact Removal from EEG - a Mixed Approach Based on Double Blind Source Separation and Support Vector Machine, Proceedings of 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), pp. 5383-5386, Buenos Aires, Argentina, August 31- September 4, 2010.
8. Hongbin Yu, Hongtao Lu, Tian Ouyang, Hongjun Liu, Bao-Liang Lu: Vigilance Detection Based on Sparse Representation of EEG, Proceedings of 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), pp. 2439-2442, Buenos Aires, Argentina, August 31- September 4, 2010.
9. Xiao-Chen Lian, Zhiwei Li, Bao-Liang Lu, Lei Zhang: Max-Margin Dictionary Learning for Multiclass Image Categorization, Proceedings of the 11th Europen Conference on Computer Vision (ECCV2010), Hersonissos, Heraklion, Crete, Greece, September 5-11, 2010.
10. Shaodian Zhang, Hai Zhao, Guodong Zhou and Bao-Liang Lu, Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection, CoNLL-2010, pp.92-99, Uppsala, Sweden, July 15-16, 2010.
11. Cong Hui, Hai Zhao, Yan Song, Bao-Liang Lu, An Empirical Study on Development Set Selection Strategy for Machine Translation Learning, WMT-2010, pp.67-71, Uppsala, Sweden, July 15-16, 2010.
12. Jian Zhang, Hai Zhao, and Bao-Liang Lu, A Comparative Study on Two Large-Scale HierarchicalText Categorization Tasks’ Solutions, Proceedings of International Workshop on Web Information Processing (IWWIP2010), Qingdao, China, July 11-14, 2010.
13. Xiao-Lin Wang and Bao-Liang Lu, Flatten hierarchies large-scale hierarchical text categorization, Proceedings of Fifth International Conference on Digital Information Management (ICDIM2010), pp. 139-144, Thunder Bay, Canada, July 5-8, 2010.
14. Tianqi Zhang, Bao-Liang Lu: Selecting Optimal Orientations of Gabor Wavelet Filters for Facial Image Analysis. Proceedings of International Conferenvce on Image and Signal Processing (ICISP 2010), pp. 218-227, Toris-Rivieres, Canada, June 30-July 2, 2010.
15. Mu Li, James Kwok, and Bao-Liang Lu. Making Large-Scale Nystr?m Approximation Possible. Proceedings of the Twenty-Seventh International Conference on Machine Learning (ICML 2010), Haifa, Israel, June 21-24, 2010.
16. Gang Jin, Qi Kong, Jian Zhang, Xiaolin Wang, Cong Hui, Hai Zhao, and Bao-Liang Lu, Multiple Strategies for NTCIR-08 Patent Mining at BCMI, Proceedings of the 8th NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retrieval, Question Answering, and Cross-Lingual Information Access, Tokyo, Japan, June 15-18, 2010.
17. Mu Li, James Kwok, and Bao-Liang Lu. Online multiple instance learning with no regret. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13-18, 2010.
18. Xiao-Chen Lian, Zhiwei Li, Changhu Wang,Bao-Liang Lu, Lei Zhang: Probabilistic Models for Supervised Dictionary Learning, Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13-18, 2010.
19. Minzhang Huang, Hai Zhao,Bao-Liang LuPruning Training Samples Using a Supervised Clustering Algorithm, Lecture Notes in Computer Science, vol. 6064, pp. 250-257, 2010.
20. Wen-Yun Yang, James T. Kwok,Bao-Liang Lu: Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm. Proceedings of 2010 SIAM International Conference on Data Mining (SDM 2010), pp. 106-117, April 29-May 1, 2010.
21. Yang Yang, Bao-Liang Lu: Protein Subcellular Multi-Localization Prediction Using a Min-Max Modular Support Vector Machine. International Journal of Neural Systems, vol. 20, no. 1, pp. 13-28, 2010.
22. Hai Zhao, Changning Huang, Mu Li, Bao-Liang Lu: A Unified Character-Based Tagging Framework for Chinese Word Segmentation. ACM Transactions on Asian Language Information Processing (TALIP) , vol. 9, no. 2, pp. 1-32, 2010.
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2009

1. Jing Li and Bao-Liang Lu, “An Adaptive Image Euclidean Distance”, Pattern Recognition, vol. 42, pp. 349-357, 2009.
2. Yun Li and Bao-Liang Lu, “Feature selection based on loss margin of nearest neighbor classification”, Pattern Recognition, vol. 42, pp. 1914-1921, 2009.
3. Dandan Song, Yang Yang, Bin Yu, Binglian Zheng, Zhidong Deng, Bao-Liang Lu, Xuemei Chen, Tao Jiang: Computational prediction of novel non-coding RNAs in Arabidopsis thaliana. BMC Bioinformatics, vol. 10 (S-1), S-36, 2009.
4. Bao-Liang Lu, Xiao-Lin Wang, and Masao Utiyama, “Incorporating prior knowledge into learning by dividing training data”, Frontiers of Computer Science, vol. 3, No. 1, pp. 109-122, 2009.
5. Bao-Liang Lu and Xiao-Lin Wang, “A Parallel and Modular Pattern Classification Framework for Large-Scale Problems”, in C. H. Chen (Ed.), Handbook of Pattern Recognition and Computer Vision (4th Edition), pp. 725-746, World Scientific, 2009.
6. Mu Li and Bao-Liang Lu, “Emotion Classification Based on Gamma-band EEG”, in Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society，pp. 1323-1326, Mineapolis, USA, 2009.
7. Jia-Cheng Guo, Bao-Liang Lu, Zhi-Wei Li, and Lei Zhang, "LogisticLDA: Regularizing Latent Dirichlet Allocation by Logistic Regression", in Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, pp. 160-169, Hong Kong, 2009.
8. Wei-Ming Liang, Chang-Ning Huang, Mu Li and Bao-Liang Lu, “Extracting Keyphrases from Chinese News Articles Using TextRank and Query Log Knowledge”, in Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, pp. 733-740, Hong Kong, 2009.
9. Shaojie Shi, Bao-Liang Lu,“EEG Signal Classification during Listening to Native and Foreign Languages Songs”, 4th International IEEE EMBS Conference on Neural Engineering, 2009, Antalya, Turkey, pp. 440-443, 2009.
10. Zheng Ji and Bao-Liang Lu, “Gender Classification Based on Support Vector Machine with Automatic Confidence”, in Proceedings of the 16th International Conference on Neural Information Processing, pp. 685-692, Bangkok, Thailand, 2009.
11. Chao Ma, Bao-Liang Lu, and Masao Utiyama, “Incorporating prior knowledge into task decomposition for large-scale patent classification”, in Proceedings of 6th International Symposium on Neural Networks, LNCS5552, pp. 784-793, 2009.
12. Yang Yang and Bao-Liang Lu, “Prediction of protein subcellular multi-localization by using a min-max modular support vector machine”, in Yu and Sanchez (Eds.), Advances in Computational Intelligence, AISC 61, pp. 133-143, Springer, 2009.
13. Yue Wang, Bao-Liang Lu, and Zhi-Fei Ye, “Module combination based on decision tree in min-max modular network, in Proceedings of International Conference on Neural Computation, pp. 555-558, Madeira, Portugal, 2009.
14. Zheng Ji, Xiao-Chen Lian, and Bao-Liang Lu, " Gender Classification by Fusion of Face and Hair Feature”, in Marid and Chacon (Eds.), State of the Art in Face Recognition, In-Teh, Vienna, Austria，pp. 215-230, 2009.
15. Jia-Wei Fu, Li-Chen Shi, and Bao-Liang Lu, “A survey on EEG-based vigilance analysis and estimation”, Chinese Journal of Biomedical Engineering (in Chinese), vol. 28, no. 4, pp. 589-596, 2009.
16. Zhi-Fei Ye, Yi-Min Wen, and Bao-Liang Lu, “A survey of imbalanced pattern classification problems”, CAAI Transactions on Intelligent Systems (in Chinese), vol. 4, no. 2, pp. 148-156, 2009.
17. He Sun and Bao-Liang Lu, “Gender Classification Based on Local Gabor Binary Mapping and Support Vector Machine”, Computer Engineering (in Chinese), vol. 35(2), pp. 210-213, 2009.
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2008

1. L.C. Shi, B.L. Lu, "Dynamic Clustering for Vigilance Analysis Based on EEG", 30-th Annual International Conference of the Engineering in Medicine and Biology Society, Vancouver , British Columbia , Canada , pp. 54-57, 2008.
2. M. Li, G.W. Fu, B.L. Lu, "Estimating Vigilance in Driving Simulation using Probabilistic PCA"，30-th Annual International Conference of the Engineering in Medicine and Biology Society, Vancouver, British Columbia, Canada, pp. 5000-5003, 2008.
3. X. Chu, C. Ma, J. Li, B. L. Lu, M. Utiyama and H. Isahara, "Large-Scale Patent Classification with Min-Max Modular Support Vector Machines", Proc. of International Joint Conference on Neural Networks (IJCNN), vol.1, pp.3972-3979, HongKong, China, 2008.
4. B. Xia, H. Sun and B. L. Lu, "Multi-view Gender Classification based on Local Gabor Binary Mapping Pattern and Support Vector Machines", Proc. of International Joint Conference on Neural Networks (IJCNN), vol.1,pp.3388-3395, HongKong, China, 2008.
5. W. Y. Yang and B. L. Lu, "A string kernel framework with feature selection for SVM protein classification", Proc. of the Sixth Asia Pacific Bioinformatics Conference (APBC), vol.6:9-18, Kyoto, Japan, 2008.
6. Y. P. Li and B. L. Lu. "Semantic similarity definition over gene ontology by further mining of the information content", Proc. of the Sixth Asia Pacific Bioinformatics Conference (APBC), vol.6:155-164, Kyoto, Japan, 2008.
7. K. Wu, X. Lin and B. L. Lu. "Cross language text categorization using a bilingual lexicon", Proc. of the Third International Joint Conference on Natural Language Processing (IJCNLP). India, 2008.
8. Yang Yang, B. L. Lu and Wen-Yun Yang, "Classification of protein sequences based on word segmentation methods", Proc. of the Sixth Asia Pacific Bioinformatics Conference (APBC), vol.6:177-186, Kyoto, Japan, 2008.
9. Cheng. Cong and B. L. Lu, “Partition of Sample Space with Perceptrons”, Computer Simulation (in Chinese), vol. 25(2), pp. 96-99, 2008.
10. Ji-Lin Li and Bao-Liang Lu, “Design of FIR Filters in Complex Domain by Neural Networks”, Computer Simulation (in Chinese), vol. 25(2), pp. 175-177, 2008.
11. K. Wu, B. L. Lu, Masao Uchiyama, and Hitoshi Isahara, "An empirical comparison of min-max-modular k-NN with different voting methods to large-scale text categorization", Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol.12, no.7, pp.647-655, 2008.
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2007

1. J. Luo, Y. Ma, E. Takikawa, S. H Lao, M. Kawade and B. L. Lu. "Person-specific SIFT features for face recognition", International Conference on Acoustic, Speech and Signal Processing (ICASSP2007), vol.2, pp.593-596, Hawaii, 2007.
2. K. Wu, B. L. Lu, "A probabilistic approach to feature selection for multi-class text categorization", Proc. of Fourth International Symposium Neural Networks (ISNN 2007), LNCS, Vol.4491: 1310-1317, Nanjing, China, 2007.
3. Y. M. Wen, and B. L. Lu, "A confident majority voting strategy for parallel and modular support vector machines", Proc. of Fourth International Symposium Neural Networks (ISNN 2007), LNCS, Vol. 4493: 525-534, Nanjing, China, 2007.
4. Y. M. Wen and B. L. Lu, "Incremental Learning of Support Vector Machines by Classifier Combining", Proc. of 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2007), LNCS, vol.4426: 904-911, Nanjing, China, 2007.
5. K. Wu and B. L. Lu, "Cross-Lingual Document Clustering", Proc. of 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2007), LNCS, vol.4426: 956-963, Nanjing, China, 2007.
6. Li-Chen Shi, Hong Yu, and Bao-Liang Lu, "Semi-Supervised Clustering for Vigilance Analysis Based on EEG," Proceedings of International Joint Conference on Neural Networks(IJCNN2007), pp. 1518-1523, Orlando, US, Aug. 2007.

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2006

1. W. Y. Yang, B. L. Lu and Y. Yang, "A comparative study on feature extraction from protein sequences for subcellular localization prediction", Proceedings of 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2006)，Toronto，Canada，2006.
2. K. Chen, B. L. Lu and J. Kwok, "Efficient classification of multi-label and imbalanced data using min-max modular classifiers", Proc. of IEEE World Congress on Computation Intelligence, pp.1770-1775, Vancoudar, Canada, July 16-21, 2006.
3. J. Li and B. L. Lu, "A new supervised clustering algorithm based on min-max modular network with gaussian-zero-crossing functions", Proc. of 2006 IEEE World Congress on Computation Intelligent, pp.786-793, Vancouver, Canada, July 16-21, 2006.
4. Y. Li, B. L. Lu and Z. F. Wu, "A hybrid method of unsupervised feature selection based on ranking". International Conference on Pattern Recognition 2006 (ICPR2006), Vol.2, pp.687-690, Hongkong, August 20-24, 2006.
5. H. C. Lian, B. L. Lu, "Multi-view gender classification using local binary patterns and support vector machines", Lecture Notes in Computer Science, 3972, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II, pp.202-209, 2006.
6. J. Luo, B. L. Lu, "Gender recognition using a min-max modular support vector machine with equal clustering", Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3972, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II, pp.210-215, 2006
7. Y. Yang, B. L. Lu, "Prediction of protein subcellular multi-locations with a min-max modular support vector machine", Lecture Notes in Computer Science, 3973,Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III, pp. 667-673, 2006.
8. H. Zhao, B. L. Lu, "A modular reduction method for k-NN algorithm with self-recombination learning", Lecture Notes in Computer Science, 3971, Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings, pp.537-544, 2006.
9. Y. Li, B. L. Lu, Z. F. Wu. "Hierarchical Fuzzy Filter Method for Unsupervised Feature Selection". Journal of Intelligent and Fuzzy Systems, 2006.
10. Z. G. Fan and B. L. Lu, "Fast Learning for Statistical Face Detection", ICONIP2006, Lecture Notes in Computer Science, LNCS 4233, pp. 187-196, 2006.
11. Hong Shen, B. L. Lu, Masao Utiyama and Hitoshi Isahara, "Comparison and Improvements of Feature Extraction Methods for Text Categorization", Computer Simulation (in Chinese), vol. 23(3), pp. 222-224, 2006.
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2005

1. Z. G. Fan and B. L. Lu, "Fast Recognition of Multi-View Faces with Feature Selection", 10th IEEE International Conference on Computer Vision (ICCV’05), vol. 1, pp. 76-81, 2005.
2. H. C. Lian and B. L. Lu, "An algorithm for pruning redundant modules in min-max modular network", International Joint Conference on Neural Networks (IJCNN2005), pp.1983-1988, Montréal, Québec, Canada, July 31-August 4, 2005.
3. F. Y. Liu, K. Wu, H. Zhao, and B. L. Lu, "Fast text categorization with min-max modular support vector machines", International Joint Conference on Neural Networks (IJCNN2005), Vol. 1, pp.570-575, Montréal, Québec, Canada, July 31-August 4, 2005.
4. Y. Yang and B. L. Lu, "Extracting features from protein sequences using chinese segmentation techniques for subcellular localization", Proceedings of 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2005), pp. 288-295, San Diego, California, USA, November 14-15, 2005.
5. F. Y. Liu, K, A. Wang, B. L. Lu, M. Utiyama, and H. Isahara, "Efficient Text Categorization Using a Min-Max Modular Support Vector Machine"，in Human Interaction With Machine, Hommel, G and Shen H. Y. Eds.,Springer, pp. 13-22, 2005.
6. H. Zhao, B. L. Lu, "Improvement on Response Performance of Min-Max Modular Classifier by Symmetric Module Selection", Proceedings of Second International Symposium Neural Networks (ISNN’05), LNCS, Vol. 3497: 39-44, Chongqing, China, 2005.
7. J. Li, B. L. Lu, "Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function", Proceedings of Second International Symposium on Neural Networks (ISNN’05), LNCS, Vol. 3496, pp. 467-472 Chongqing, China, 2005.
8. Y. M. Wen and B. L. Lu, "A hierarchical and parallel method for training support vector machines", Proceedings of Second International Symposium on Neural Networks (ISNN’05), LNCS, 881-886, Chongqing, China, 2005.
9. Y. Yang, B. L. Lu, "Structure Pruning Strategies for Min-Max Modular Network", Proceedings of Second International Symposium on Neural Networks (ISNN’05), LNCS, vol. 3496, pp. 646-651, Chongqing, China, 2005.
10. K. A. Wang, H. Zhao and B. L. Lu, "Task Decomposition Using Geometric Relation for Min-Max Modular SVMs", Proceedings of Second International Symposium on Neural Networks (ISNN’05), LNCS, vol. 3496, pp. 887-892, Chongqing, China, 2005.
11. H. Zhao and B. L. Lu, "A General Procedure for Combining Binary Classifiers and Its Performance Analysis", Proceeding s of the First International Conference on Natural Computation (ICNC’05), LNCS, vol. 3610, pp. 303-312, Changsha, China, 2005.
12. J. Li, B. L. Lu, and M. Ichikawa, "An algorithm for pruning redundant modules in min-max modular network with GZC function", Proceedings of the First International Conference on Natural Computation (ICNC’05), LNCS, vol.3610, pp.293-302, Changsha, China, 2005.
13. Z. G. Fan and B. L. Lu, "Multi-View Face Recognition with Min-Max Modular SVMs", Proceedings of the First International Conference on Natural Computation (ICNC’05), LNCS, vol. 3611, pp. 396-399, Changsha, China, 2005.
14. H. C. Lian and B. L. Lu, "Gender Recognition Using a Min-Max Modular SVM", Proceedings of the First International Conference on Natural Computation (ICNC’05), LNCS, vol. 3611, pp. 433-436, Changsha, China, 2005.
15. Y. K. Chen, H. Zhao and B. L. Lu, "On improvement on generalization performance of classifier by using empirical risk", 2nd International Conference on Neural Networks and Brain, vol.1 pp. 41-46, Beijing, China, 2005.
16. H. C. Lian and B. L. Lu, "Age estimation using a min-max modular support vector machine", 12th International Conference on Neural Information Processing (ICONIP 2005), pp.83-88, Taipei, October 30-November 2, 2005.
17. Y. M. Wen, B. L. Lu and H. Zhao, "Equal clustering makes min-max modular support vector machine more efficient", 12th International Conference on Neural Information Processing (ICONIP 2005), pp.77-82, Taipei, October 30-November 2, 2005.
18. H. Zhao, B. L. Lu, Y. M. Wen and K. A. Wang, "On effective decomposition of training data sets for min-Max modular classifier", 12th International Conference on Neural Information Processing (ICONIP 2005), pp.343-348, Taipei, October 30-November 2, 2005.
19. H. Zhao and B. L. Lu, "Determination of hyperplane by PCA for dividing training data set", 12th International Conference on Neural Information Processing (ICONIP 2005), pp.755-760, Taipei, October 30-November 2, 2005.
20. Yi-Min Wen, Yang Yang and Bao-Liang Lu, “Research on the Application of Ensemble Learning Algorithms to Incremental Learning”, Journal of Computer Research and Development (in Chinese), vol. 42, Suppl. B, pp. 222-227, 2005.
21. Hai Zhao and Bao-Liang Lu, “A Self Recombination Learning Algorithm for Min-Max Combining Classifier”, Journal of Computer Research and Development (in Chinese), vol. 42, Suppl. B, pp. 243-247, 2005.
22. Zhi-Gang Fan and Bao-Liang Lu , “Fast recognition of Multi-View Faces Based on Iterative Feature Selection”, Journal of Computer Research and Development (in Chinese), vol. 42, Suppl. B, pp. 325-329, 2005.
23. Bao-Liang Lu, Feng-Yao Liu, Masao Utiyama, and Hitoshi Isahara, “Multilabel Text categorization Using a Min-Max Modular Support Vector Machine”, Journal of Computer Research and Development (in Chinese), vol. 42, Suppl. B, pp. 361-366, 2005.
24. Yi-Min Wen, Yang Yang and Bao-Liang Lu, “Improvement Research of Min-Max Modular Support Vector Machine”, Computer Engineering and Applications (in Chinese), vol. 19, pp. 185-188, 2005

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2004

1. B. L. Lu, K. A. Wang, M. Utiyama, and H. Isahara, "A part-versus-part method for massively parallel training of support vector machines", Proc. of IEEE/INNS Int. Joint Conf. on Neural Networks (IJCNN2004), Budabest, Hungary, July 25-29, pp. 735-740, 2004.
2. Z. G. Fan and B. L. Lu, "An adjusted Gaussian skin-color model based on principle component analysis", Advances in Neural Networks-ISNN2004, Lecture Notes in Computer Science, vol. 3173, part I, pp. 804-809, 2004.
3. Y. M. Wen and B. L. Lu, "A cascade method for reducing training time and the number of support vectors", Advances in Neural Networks-ISNN2004, Lecture Notes in Computer Science, vol. 3173, part I, pp. 480-485, 2004.
4. H. Zhao and B. L. Lu, "Analysis of fault tolerance of a combining classifier", Advances in Neural Networks-ISNN2004, Lecture Notes in Computer Science , vol. 3173, 888-893, 2004.
5. B. Huang and B. L. Lu, "Fault diagnosis for industrial images using a min-max modular neural network", 11th International Conference on Neural Information Processing (ICONIP2004), Calcutta, India, Nov. 22-25, 2004, Lecture Notes in Computer Science, vol. 3316, 843-847, 2004.
6. Z. G. Fan and B. L. Lu, "Feature selection for fast image classification with support vector machines", 11th International Conference on Neural Information Processing (ICONIP2004), Calcutta, India, Nov. 22-25, 2004, Lecture Notes in Computer Science , vol. 3316, 1026-1031, 2004.
7. H. Zhao and B. L. Lu, "A modular k-nearest neighbor classification method for massively parallel text categorization", First International Symposium on Computational and Information Science, Shanghai, Dec. 16-18, 2004, Lecture Notes in Computer Science , vol. 3314, 867-872, 2004.
8. B. L. Lu, K. A. Wang, and Y. M. Wen, "Comparison of parallel and cascade methods for training support vector machines on large-scale problems" (invited paper), Proc. Of International Conference on Machine Learning and Cybernetics (ICMLC04), pp.3056-3061, Shanghai, China, Aug. 26-29, 2004
9. B. L. Lu, J. H. Shin, M. Ichikawa, 2004. Massively parallel classification of single-trial EEG signals using a min-max modular neural network. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 51 (3): 551-558.

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2003

1. B. L. Lu and K. Ito, "Converting general nonlinear programming problems into separable programming problems with feedforward neural networks", Neural Networks, vol. 16, pp. 1059-1074, 2003.
2. B. L. Lu, Q. Ma, M. Ichikawa, and H. Isahara, "Efficient part-of-speech tagging with a min-max modular neural network", Applied Intelligence, vol 19, pp. 65-81, 2003.
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2002 and before
1. B. L. Lu, M. Ichikawa, "Emergent on-line learning with a Gaussian zero-crossing discriminant function", Proceedings of the International Joint Conference on Neural Networks, 2002, 2, pp. 1263-1268.
2. Q. Ma, B. L. Lu, H. Isahara, M. Ichikawa, "Part of speech tagging with min-max modular neural networks", Systems and Computers in Japan, 2002, 33(7), pp.30-39.
3. B. L. Lu, J. Shin, M. Ichikawa, "Massively parallel classification of EEG signals using min-max modular neural networks", Lecture Notes in Computer Science, vol. 2130, 601-608, 2001.
4. Q. Ma, B. L. Lu, M. Murata, et al. "On-line error detection of annotated corpus using modular neural networks", Lecture Notes in Computer Science, vol. 2130, 1185-1192, 2001.
5. J. H. Shin, B. L. Lu, A. Talnov, et al. " Reading auditory discrimination behaviour of freely moving rats from hippocampal EEG", Neurocomputing, vol. 38, 1557-1566, 2001.
6. B. L. Lu, M. Ichikawa, "Emergence of learning: An approach to coping with NP-complete problems in learning", Proceedings of the International Joint Conference on Neural Networks, 2000, 4, pp.159-164.
7. B. L. Lu, M. Ichikawa, S. Hosoe, "Modular massively parallel learning framework for brain-like computers", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1999, 5, pp. 332-337.
8. Q. Ma, B. L. Lu, H. Isahara, "Part of speech tagging with min-max modular neural networks", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1999, 5, pp.356-360.
9. G. R. Ji, B. L. Lu, X. Chen, J. Wang, "Object searching in scale-space", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1999, 1, pp.565-570.
10. B. L. Lu, H. Kita, Y. Nishikawa, "Inverting feedforward neural networks using linear and nonlinear programming", IEEE Transactions on neural networks, vol. 10 (6), 1271-1290, 1999.
11. B. L. Lu, M. Ito, "Task decomposition and module combination based on class relations: A modular neural network for pattern classification", IEEE Transactions on Neural Networks, vol. 10 (5), 1244-1256, 1999.
12. B. L. Lu, M. Ito, "Task decomposition based on class relations: A modular neural network architecture for pattern classification", Lecture Notes in Computer Science, vol. 1240, 330-339, 1997.
13. Book Chapters: B. L. Lu and K. Ito, "Transformation of nonlinear programming problems into separable ones using multi-layer neural networks", Mathematics of Neural Networks: Models, Algorithms and Applications, S. W. Ellacott, J. C. Mason, and I. J. Anderson Eds., Kluwer Academic Publishers, pp. 235-239, 1997
14. B. L. Lu, K. Ito, M. Ito, "Solving inverse kinematics problem of redundant manipulators in an environment with obstacles using separable nonlinear programming", Proceedings of the Japan/USA Symposium on Flexible Automation, 1996, 1, pp.79-82.
15. B. L. Lu, K. Ito, "A Parallel and modular multi-sieving neural network architecture with multiple control networks", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1996, 2, pp. 1303-1308.
16. B. L. Lu, K. Ito, "Regularization of inverse kinematics for redundant manipulators using neural network inversions", IEEE International Conference on Neural Networks - Conference Proceedings, 1995, 5, pp. 2726-2731. [PDF]
17. B. L. Lu, H. Kita, Y. Nishikawa, "Multi-sieving neural network architecture that decomposes learning tasks automatically", IEEE International Conference on Neural Networks - Conference Proceedings, 1994, 3, pp.1319-1324.
18. B. L. Lu, Y. Bai, H. Kita, Y. Nishikawa, "Efficient multilayer quadratic perceptron for pattern classification and function approximation", Proceedings of the International Joint Conference on Neural Networks, 1993, 2, pp.1385-1388.
19. B. L. Lu, H. Kita, Y. Nishikawa, "A new method for inverting nonlinear multilayer feedforward networks", IECON Proceedings (Industrial Electronics Conference), 1991, 2, pp.1349-1354

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2004年上海交通大学施耐德教学奖；
2011年中国国际工业博览会高校作品二等奖；
2012年亚太神经网络联合会杰出服务奖；
2018年IEEE Transactions on Autonomous Mental Development Outstanding Paper Award

IEEE Transactions on Affective Computing指导委员会委员, IEEE Transactions on Cognitive and DevelopmentalSystems副主编，《模式识别与人工知能》编辑委员会委员，亚太神经网络学会理事，