Bao-Liang
Lu
Professor,
Vice Chair
Department of
blu AT cs DOT sjtu DOT edu DOT cn
bllu AT sjtu DOT edu DOT cn
Phone.: +86-21-34205422
Office: Room 431, Dian Xin Building 3
Address:
Research Interest
Brain-like computing, neural
networks, machine learning, pattern recognition, computer vision,
brain-computer interface, natural language processing, and computational
biology.
Education Background
I received the B.S.
degree in instrument and control engineering from Qingdao University of Science
and
Work Experience
From
1982 to 1986, I was with the Qingdao University of Science and Technology. From
April 1994 to March 1999, I was a Frontier Researcher at the
Teaching
1.
Neural Network Theory and Applications
2.
Data Structure and Algorithm Analysis
Major Grants
1. Dry-electrode-based Wireless Wearable EEG-cap and Its Application to Drivers' Vigilance Monitor System
Principal Investigator: Bao-Liang Lu
Grant Number: 09511502400
Agency: Science and Technology Commission of Shanghai Municipality
Period: July. 1, 2009 to June 30, 2011
2. The Basic Mechanism Research of Visual Information Processing
Principal Investigator: Bao-Liang Lu
Grant Number: 2009CB320901
Agency: National Basic Research Program (973) of China
Period: Jan. 1, 2009 to Dec. 31, 2013
3. EEG Based Vigilance Estimation and Prediction for Drivers
Principal Investigator: Bao-Liang Lu
Grant Number: NSFC 90820018
Agency: National Science Foundation of China
Period: Jan. 1, 2009 to Dec. 31, 2011
4. Integrated platform for analysis of metagenomic and
metabonomic data and study on metabolic disease
Principal Investigator: Bao-Liang Lu
Grant Number: NSFC 2008AA02Z315
Agency: National High-Tech Research Program (863) of China
Period: Jan. 1, 2008 to Dec. 31, 2010.
5. Learning algorithm for Large-scale, multi-label, and imbalanced classification problems
Principal Investigator: Bao-Liang Lu
Grant Number: NSFC 60773090
Agency: National Science Foundation of China
Period: Jan. 1, 2008 to Dec. 31, 2010.
6. Task decomposition and module combination for massively parallel pattern classifiers
Principal Investigator: Bao-Liang Lu
Grant Number: NSFC 60473040
Agency: National Science Foundation of China
Period: Jan. 1, 2005 to Dec. 31, 2007.
7. Incremental learning model
Principal Investigator: Bao-Liang Lu
Grant Number: NSFC 60375022
Agency: National Science Foundation of China
Period: Jan. 1, 2004 to Dec. 31, 2006.
Publication
2011
1. Tian-Xiang Wu, Xiao-Chen Lian, and Bao-Liang Lu, Multi-view Gender Classification Using Symmetry of Facial Images, to appear in Neural Computing and Applications.[PDF]
2. Bing Li, Xiao-Chen Lian, and Bao-Liang Lu, Gender Classification by Combining Clothing, Hair and Face Organs Classifiers, to appear in Neurocomputing. [PDF]
3. Bing Li, Rong Xiao, Zhiwei Li, Rui Cai, Bao-Liang Lu, and Lei Zhang, Rank-SIFT: Learning to Rank Repeatable Local Interest Points, to appear in Proc. of 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 20-25, 2011.[PDF]
4. Mu Li, Xiao-Chen Lian, James T. Kwok, and Bao-Liang Lu, Time and Space Efficient Spectral Clustering via Column Sampling, to appear in Proc. of 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 20-25, 2011. [PDF]
5. Dan Nie, Xiao-Wei Wang, Li-Chen Shi, and Bao-Liang Lu, EEG-based Emotion Recognition during Watching Movies, in Proc. of 5th International IEEE EMBC Conference on Neural Engineering (NER), pp. 667-670, Cancun, Mexico, April 27-May 1, 2011.[PDF]
2010
1. Yan-Ming Tang and Bao-Liang Lu, Age Classification Combining Contour and Texture Feature, to appear in Proceedings of 17th International Conference on Neural Information Processing (ICONIP2010), Sydney, Australia, November 22-25, 2010.[PDF]
2. Tian-Xiang Wu and Bao-Liang Lu, Multi-view Gender Classification Using Hierarchical Classifiers Structure, to appear in Proceedings of 17th International Conference on Neural Information Processing (ICONIP2010), Sydney, Australia, November 22-25, 2010. [PDF]
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.[PDF]
4. Xuezhe Ma, Xiaotian Zhang, Hai Zhao and Bao-Liang Lu, Dependency Parser for Chinese Constituent Parsing, CIPS-SIGHAN-2010, August, 2010, Beijing, China.[PDF]
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.. [PDF]
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.[PDF]
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. [PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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, 201.[PDF]
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.[PDF]
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.[PDF]
23. Zheng Ji and Bao-Liang Lu: “A Support Vector Machine Classifier with Automatic Confidence and Its Application to Gender Classification” to appear in Neuraocomputing.[PDF]
2009
1. Jing Li and Bao-Liang Lu, “An Adaptive Image Euclidean Distance”, Pattern Recognition, vol. 42, pp. 349-357, 2009. [PDF]
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. [PDF]
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.[PDF]
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.[PDF]
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.
[PDF]
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.[PDF]
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.
[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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.[PDF]
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,
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, 2008, Vancouver, British Columbia, Canada, pp.
5000-5003 [PDF]
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 [PDF]
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,
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,
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).
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,
9. Cheng. Cong and B. L. Lu, “Partition of Sample Space with Perceptrons”, Computer Simulation (in Chinese), vol. 25(2), pp. 96-99, 2008[PDF]
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[PDF]
2007
1.
J. Luo, Y. Ma,
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,
3. 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. (ISNN 2007) [PDF]
4. 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. [PDF]
5. 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. [PDF]
6.
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. [PDF]
7.
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,
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. [PDF]
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,
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,
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, 2006, pp.202-209. [PDF]
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, 2006, pp.210-215. [PDF]
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, 2006, pp. 667-673. [PDF]
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,
2006, pp.537-544. [PDF]
9.
Y. Li, B. L. Lu,
Z. F. Wu. Hierarchical Fuzzy Filter Method for Unsupervised Feature Selection.
Journal of Intelligent and Fuzzy Systems (in press).
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. [PDF]
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[PDF]
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.
[PDF]
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,
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. [PDF]
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. [PDF]
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,
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. [PDF]
8.
Y. M. Wen and B. L.
Lu, "A hierarchical an parallel method for training support vector
machines", Proceedings of Second International Symposium on Neural Networks
(ISNN’05), LNCS, 881-886,
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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,
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. [PDF]
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,
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,
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.
范志刚，
21.
22.
文益民，
23.
赵海，
24.
文益民，
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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,
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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.
[PDF]
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. [PDF]
5.
J. H. Shin, B. L. Lu,
A. Talnov, et al. "
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
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. [PDF]
19.
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. [PDF]
20.
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. [PDF]
Links
[Last
updated: May, 2008]