| 2009 |
|---|
| 63 | EE | Bao-Liang Lu,
Xiaolin Wang,
Masao Utiyama:
Incorporating prior knowledge into learning by dividing training data.
Frontiers of Computer Science in China 3(1): 109-122 (2009) |
| 62 | EE | Jing Li,
Bao-Liang Lu:
An adaptive image Euclidean distance.
Pattern Recognition 42(3): 349-357 (2009) |
| 2008 |
|---|
| 61 | EE | Ke Wu,
Bao-Liang Lu:
A Refinement Framework for Cross Language Text Categorization.
AIRS 2008: 401-411 |
| 60 | EE | Yuan-Peng Li,
Bao-Liang Lu:
Semantic Similarity Definition over Gene Ontology by Further Mining of the Information Content.
APBC 2008: 155-164 |
| 59 | EE | Yang Yang,
Bao-Liang Lu,
Wen-Yun Yang:
Classification of Protein Sequences Based on Word Segmentation Methods.
APBC 2008: 177-186 |
| 58 | EE | Wen-Yun Yang,
Bao-Liang Lu:
String Kernels with Feature Selection for SVM Protein Classification.
APBC 2008: 9-18 |
| 57 | EE | Bin Xia,
He Sun,
Bao-Liang Lu:
Multi-view gender classification based on local Gabor binary mapping pattern and support vector machines.
IJCNN 2008: 3388-3395 |
| 56 | EE | Xiao-Lei Chu,
Chao Ma,
Jing Li,
Bao-Liang Lu,
Masao Utiyama,
Hitoshi Isahara:
Large-scale patent classification with min-max modular support vector machines.
IJCNN 2008: 3973-3980 |
| 55 | EE | Ke Wu,
Bao-Liang Lu,
Masao Utiyama,
Hitoshi Isahara:
An empirical comparison of min-max-modular k -NN with different voting methods to large-scale text categorization.
Soft Comput. 12(7): 647-655 (2008) |
| 2007 |
|---|
| 54 | EE | Jing Li,
Bao-Liang Lu:
A Framework for Multi-view Gender Classification.
ICONIP (1) 2007: 973-982 |
| 53 | EE | Yang Yang,
Bao-Liang Lu:
Incorporating Domain Knowledge into a Min-Max Modular Support Vector Machine for Protein Subcellular Localization.
ICONIP (2) 2007: 827-836 |
| 52 | EE | Li-Chen Shi,
Hong Yu,
Bao-Liang Lu:
Semi-Supervised Clustering for Vigilance Analysis Based on EEG.
IJCNN 2007: 1518-1523 |
| 51 | EE | Zhi-Fei Ye,
Bao-Liang Lu:
Learning Imbalanced Data Sets with a Min-Max Modular Support Vector Machine.
IJCNN 2007: 1673-1678 |
| 50 | EE | Feng Zhou,
Bao-Liang Lu:
Learning Concepts from Large-Scale Data Sets by Pairwise Coupling with Probabilistic Outputs.
IJCNN 2007: 524-529 |
| 49 | EE | Ke Wu,
Bao-Liang Lu,
Masao Uchiyama,
Hitoshi Isahara:
A Probabilistic Approach to Feature Selection for Multi-class Text Categorization.
ISNN (1) 2007: 1310-1317 |
| 48 | EE | Yimin Wen,
Bao-Liang Lu:
A Confident Majority Voting Strategy for Parallel and Modular Support Vector Machines.
ISNN (3) 2007: 525-534 |
| 47 | EE | Yimin Wen,
Bao-Liang Lu:
Incremental Learning of Support Vector Machines by Classifier Combining.
PAKDD 2007: 904-911 |
| 46 | EE | Ke Wu,
Bao-Liang Lu:
Cross-Lingual Document Clustering.
PAKDD 2007: 956-963 |
| 45 | EE | Yun Li,
Bao-Liang Lu:
Feature Selection for Identifying Critical Variables of Principal Components Based on K-Nearest Neighbor Rule.
VISUAL 2007: 193-204 |
| 44 | EE | Bao-Liang Lu,
Jing Li:
A Min-Max Modular Network with Gaussian-Zero-Crossing Function.
Trends in Neural Computation 2007: 285-313 |
| 43 | EE | Hui-Cheng Lian,
Bao-Liang Lu:
Multi-View Gender Classification Using Multi-Resolution Local Binary Patterns and Support Vector Machines.
Int. J. Neural Syst. 17(6): 479-487 (2007) |
| 42 | EE | Yun Li,
Bao-Liang Lu,
Zhong-Fu Wu:
Hierarchical fuzzy filter method for unsupervised feature selection.
Journal of Intelligent and Fuzzy Systems 18(2): 157-169 (2007) |
| 2006 |
|---|
| 41 | | Jun Wang,
Zhang Yi,
Jacek M. Zurada,
Bao-Liang Lu,
Hujun Yin:
Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part I
Springer 2006 |
| 40 | | Jun Wang,
Zhang Yi,
Jacek M. Zurada,
Bao-Liang Lu,
Hujun Yin:
Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part II
Springer 2006 |
| 39 | | Jun Wang,
Zhang Yi,
Jacek M. Zurada,
Bao-Liang Lu,
Hujun Yin:
Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part III
Springer 2006 |
| 38 | EE | Wen-Yun Yang,
Bao-Liang Lu,
Yang Yang:
A Comparative Study on Feature Extraction from Protein Sequences for Subcellular Localization Prediction.
CIBCB 2006: 1-8 |
| 37 | EE | Zhi-Gang Fan,
Bao-Liang Lu:
Fast Learning for Statistical Face Detection.
ICONIP (2) 2006: 187-196 |
| 36 | EE | Yun Li,
Bao-Liang Lu,
Zhong-Fu Wu:
A Hybrid Method of Unsupervised Feature Selection Based on Ranking.
ICPR (2) 2006: 687-690 |
| 35 | EE | Ken Chen,
Bao-Liang Lu,
James T. Kwok:
Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers.
IJCNN 2006: 1770-1775 |
| 34 | EE | Jing Li,
Bao-Liang Lu:
A New Supervised Clustering Algorithm Based on Min-Max Modular Network with Gaussian-Zero-Crossing Functions.
IJCNN 2006: 786-793 |
| 33 | EE | Hai Zhao,
Bao-Liang Lu:
A Modular Reduction Method for k-NN Algorithm with Self-recombination Learning.
ISNN (1) 2006: 537-544 |
| 32 | EE | Hui-Cheng Lian,
Bao-Liang Lu:
Multi-view Gender Classification Using Local Binary Patterns and Support Vector Machines.
ISNN (2) 2006: 202-209 |
| 31 | EE | Jun Luo,
Bao-Liang Lu:
Gender Recognition Using a Min-Max Modular Support Vector Machine with Equal Clustering.
ISNN (2) 2006: 210-215 |
| 30 | EE | Yang Yang,
Bao-Liang Lu:
Prediction of Protein Subcellular Multi-locations with a Min-Max Modular Support Vector Machine.
ISNN (2) 2006: 667-673 |
| 2005 |
|---|
| 29 | | Yang Yang,
Bao-Liang Lu:
Extracting Features from Protein Sequences Using Chinese Segmentation Techniques for Subcellular Localization.
CIBCB 2005: 288-295 |
| 28 | EE | Zhi-Gang Fan,
Bao-Liang Lu:
Fast Recognition of Multi-View Faces with Feature Selection.
ICCV 2005: 76-81 |
| 27 | EE | Jing Li,
Bao-Liang Lu,
Michinori Ichikawa:
An Algorithm for Pruning Redundant Modules in Min-Max Modular Network with GZC Function.
ICNC (1) 2005: 293-302 |
| 26 | EE | Hai Zhao,
Bao-Liang Lu:
A General Procedure for Combining Binary Classifiers and Its Performance Analysis.
ICNC (1) 2005: 303-312 |
| 25 | EE | Zhi-Gang Fan,
Bao-Liang Lu:
Multi-view Face Recognition with Min-Max Modular SVMs.
ICNC (2) 2005: 396-399 |
| 24 | EE | Hui-Cheng Lian,
Bao-Liang Lu,
Erina Takikawa,
Satoshi Hosoi:
Gender Recognition Using a Min-Max Modular Support Vector Machine.
ICNC (2) 2005: 438-441 |
| 23 | EE | Jing Li,
Bao-Liang Lu,
Michinori Ichikawa:
Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function.
ISNN (1) 2005: 467-472 |
| 22 | EE | Yang Yang,
Bao-Liang Lu:
Structure Pruning Strategies for Min-Max Modular Network.
ISNN (1) 2005: 646-651 |
| 21 | EE | Yimin Wen,
Bao-Liang Lu:
A Hierarchical and Parallel Method for Training Support Vector Machines.
ISNN (1) 2005: 881-886 |
| 20 | EE | Kaian Wang,
Hai Zhao,
Bao-Liang Lu:
Task Decomposition Using Geometric Relation for Min-Max Modular SVMs.
ISNN (1) 2005: 887-892 |
| 19 | EE | Hai Zhao,
Bao-Liang Lu:
Improvement on Response Performance of Min-Max Modular Classifier by Symmetric Module Selection.
ISNN (2) 2005: 39-44 |
| 2004 |
|---|
| 18 | EE | Hai Zhao,
Bao-Liang Lu:
A Modular k-Nearest Neighbor Classification Method for Massively Parallel Text Categorization.
CIS 2004: 867-872 |
| 17 | EE | Zhi-Gang Fan,
Kaian Wang,
Bao-Liang Lu:
Feature Selection for Fast Image Classification with Support Vector Machines.
ICONIP 2004: 1026-1031 |
| 16 | EE | Bin Huang,
Bao-Liang Lu:
Fault Diagnosis for Industrial Images Using a Min-Max Modular Neural Network.
ICONIP 2004: 842-847 |
| 15 | EE | Yimin Wen,
Bao-Liang Lu:
A Cascade Method for Reducing Training Time and the Number of Support Vectors.
ISNN (1) 2004: 480-486 |
| 14 | EE | Zhi-Gang Fan,
Bao-Liang Lu:
An Adjusted Gaussian Skin-Color Model Based on Principal Component Analysis.
ISNN (1) 2004: 804-809 |
| 13 | EE | Hai Zhao,
Bao-Liang Lu:
Analysis of Fault Tolerance of a Combining Classifier.
ISNN (1) 2004: 888-893 |
| 2003 |
|---|
| 12 | | Bao-Liang Lu,
Qing Ma,
Michinori Ichikawa,
Hitoshi Isahara:
Efficient Part-of-Speech Tagging with a Min-Max Modular Neural-Network Model.
Appl. Intell. 19(1-2): 65-81 (2003) |
| 11 | EE | Bao-Liang Lu,
Koji Ito:
Converting general nonlinear programming problems into separable programming problems with feedforward neural networks.
Neural Networks 16(7): 1059-1074 (2003) |
| 2002 |
|---|
| 10 | EE | Qing Ma,
Bao-Liang Lu,
Hitoshi Isahara,
Michinori Ichikawa:
Part of speech tagging with min-max modular neural networks.
Systems and Computers in Japan 33(7): 30-39 (2002) |
| 2001 |
|---|
| 9 | EE | Qing Ma,
Bao-Liang Lu,
Masaki Murata,
Michinori Ichikawa,
Hitoshi Isahara:
On-Line Error Detection of Annotated Corpus Using Modular Neural Networks.
ICANN 2001: 1185-1192 |
| 8 | EE | Bao-Liang Lu,
Jonghan Shin,
Michinori Ichikawa:
Massively Parallel Classification of EEG Signals Using Min-Max Modular Neural Networks.
ICANN 2001: 601-608 |
| 7 | EE | Jonghan Shin,
Bao-Liang Lu,
Arkadi Talnov,
Gen Matsumoto,
Jurij Brankack:
Reading auditory discrimination behaviour of freely moving rats from hippocampal EEG.
Neurocomputing 38-40: 1557-1566 (2001) |
| 2000 |
|---|
| 6 | EE | Bao-Liang Lu,
Michinori Ichikawa:
Emergence of Learning: An Approach to Coping with NP-Complete Problems in Learning.
IJCNN (4) 2000: 159-164 |
| 1999 |
|---|
| 5 | EE | Bao-Liang Lu,
Masami Ito:
Task decomposition and module combination based on class relations: a modular neural network for pattern classification.
IEEE Transactions on Neural Networks 10(5): 1244-1256 (1999) |
| 4 | EE | Bao-Liang Lu,
H. Kita,
Y. Nishikawa:
Inverting feedforward neural networks using linear and nonlinear programming.
IEEE Transactions on Neural Networks 10(6): 1271-1290 (1999) |
| 1998 |
|---|
| 3 | | Bao-Liang Lu,
Masami Ito:
Decomposition and Parallel Learning of Imbalanced Classification Problems by Min-Max Modular Neural Network.
ICONIP 1998: 199-202 |
| 2 | | Bao-Liang Lu,
Masami Ito:
Decomposing and Parallel Learning of Large-Scale Pattern Recognition Problems using Min-Max Modular Neural Network.
NC 1998: 703-709 |
| 1997 |
|---|
| 1 | | Bao-Liang Lu,
Masami Ito:
Task Decomposition Based on Class Relations: A Modular Neural Network Architecture for Pattern Classification.
IWANN 1997: 330-339 |
