| 2026 | AAAI | MindCross: Fast New Subject Adaptation with Limited Data for Cross-subject Video Reconstruction from Brain Signals. | Xuan-Hao Liu, Yan-Kai Liu, Tianyi Zhou, Bao-Liang Lu, Wei-Long Zheng |
| 2026 | AAAI | A Multimodal EEG-Eye Movement Model for Automatic Depression Detection. | Hao-Long Yin, Jian-Ming Zhang, Ren-Jie Dai, Wei-Long Zheng, Qinyu Lv, Zhenghui Yi, Bao-Liang Lu |
| 2025 | AAAI | Multi-to-Single: Reducing Multimodal Dependency in Emotion Recognition Through Contrastive Learning. | Yan-Kai Liu, Jinyu Cai, Bao-Liang Lu, Wei-Long Zheng |
| 2025 | CogSci | Self-supervised EEG Representation Learning based on Temporal Prediction and Spatial Reconstruction for Emotion Recognition. | Ren-Jie Dai, Keya Hu, Hao-Long Yin, Bao-Liang Lu, Wei-Long Zheng |
| 2025 | CogSci | mixEEG: Enhancing EEG Federated Learning for Cross-subject EEG Classification with Tailored mixup. | Xuan-Hao Liu, Bao-Liang Lu, Wei-Long Zheng |
| 2025 | ICASSP | Gram: A Large-Scale General EEG Model for Raw Data Classification and Restoration Tasks. | Ziyi Li, Wei-Long Zheng, Bao-Liang Lu |
| 2025 | ICASSP | Multi-Source Multi-Target Domain Similarity Network for Cross-Cultural EEG Emotion Recognition. | Haiqing Hu, Hanwen Shi, Bao-Liang Lu, Wei-Long Zheng |
| 2025 | ICASSP | STAR: A Spatial-Temporal Autoencoder for EEG Restoration in Emotion Recognition. | Hao-Long Yin, Wei-Long Zheng, Bao-Liang Lu |
| 2025 | ICASSP | Multi-Scale Attention-Based Dense Spatial-Temporal Model for Emotion Induction in Response to Olfactory Stimuli. | Jian-Ming Zhang, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu |
| 2025 | ICCV | EEGMirror: Leveraging EEG Data in the Wild Via Montage-Agnostic Self-Supervision for EEG to Video Decoding. | Xuan-Hao Liu, Bao-Liang Lu, Wei-Long Zheng |
| 2025 | ICLR | NeuroLM: A Universal Multi-task Foundation Model for Bridging the Gap between Language and EEG Signals. | Weibang Jiang, Yansen Wang, Bao-Liang Lu, Dongsheng Li |
| 2025 | ICONIP | Hierarchical Emotion Transformer for Multimodal Joint Emotion Category and Intensity Recognition. | Tian-Fang Ma, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu |
| 2025 | ICONIP | Multi-session Meditative EEG Classification with Noise-Robust Self-supervision. | Zuxin Song, Fei Cheng, Mingyu Gou, Tianzhen Chen, Bao-Liang Lu, Jiang Du, Wei-Long Zheng |
| 2024 | ICASSP | Multimodal Multi-View Spectral-Spatial-Temporal Masked Autoencoder for Self-Supervised Emotion Recognition. | Pengxuan Gao, Tianyu Liu, Jia-Wen Liu, Bao-Liang Lu, Wei-Long Zheng |
| 2024 | ICASSP | Functional Emotion Transformer for EEG-Assisted Cross-Modal Emotion Recognition. | Wei-Bang Jiang, Ziyi Li, Wei-Long Zheng, Bao-Liang Lu |
| 2024 | ICASSP | CEMOAE: A Dynamic Autoencoder with Masked Channel Modeling for Robust EEG-Based Emotion Recognition. | Yu-Ting Lan, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu |
| 2024 | ICASSP | Temporal-Spatial Prediction: Pre-Training on Diverse Datasets for EEG Classification. | Ziyi Li, Li-Ming Zhao, Wei-Long Zheng, Bao-Liang Lu |
| 2024 | ICLR | Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI. | Wei-Bang Jiang, Li-Ming Zhao, Bao-Liang Lu |
| 2024 | ICONIP | A Multi-task Emotion Recognition Model Based on Continuously Labeled EEG Signals. | Rong-Fei Gu, Yi-Dong Zhao, Li-Ming Zhao, Wei-Long Zheng, Bao-Liang Lu |
| 2024 | IJCNN | Detecting Major Depression Disorder with Multiview Eye Movement Features in a Novel Oil Painting Paradigm. | Tian-Fang Ma, Lu-Yu Liu, Li-Ming Zhao, Dan Peng, Yong Lu, Wei-Long Zheng, Bao-Liang Lu |
| 2023 | ICASSP | Elastic Graph Transformer Networks for EEG-Based Emotion Recognition. | Wei-Bang Jiang, Xu Yan, Wei-Long Zheng, Bao-Liang Lu |
| 2023 | ICONIP | DAformer: Transformer with Domain Adversarial Adaptation for EEG-Based Emotion Recognition with Live-Oil Paintings. | Zhong-Wei Jin, Jiawen Liu, Wei-Long Zheng, Bao-Liang Lu |
| 2023 | ICONIP | Two-Stream Spectral-Temporal Denoising Network for End-to-End Robust EEG-Based Emotion Recognition. | Xuan-Hao Liu, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu |
| 2023 | ICONIP | Naturalistic Emotion Recognition Using EEG and Eye Movements. | Jian-Ming Zhang, Jiawen Liu, Ziyi Li, Tian-Fang Ma, Yiting Wang, Wei-Long Zheng, Bao-Liang Lu |
| 2023 | IJCNN | Cross-Subject Decision Confidence Estimation from EEG Signals Using Spectral-Spatial-Temporal Adaptive GCN with Domain Adaptation. | Rong-Fei Gu, Rui Li, Wei-Long Zheng, Bao-Liang Lu |
| 2022 | ICONIP | Measuring Decision Confidence Levels from EEG Using a Spectral-Spatial-Temporal Adaptive Graph Convolutional Neural Network. | Rui Li, Yiting Wang, Bao-Liang Lu |
| 2022 | ICONIP | Few-Shot Class-Incremental Learning for EEG-Based Emotion Recognition. | Tian-Fang Ma, Wei-Long Zheng, Bao-Liang Lu |
| 2022 | IJCNN | Increasing the Stability of EEG-based Emotion Recognition with a Variant of Neural Processes. | Yan-Kai Liu, Wei-Bang Jiang, Bao-Liang Lu |
| 2021 | AAAI | Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition. | Li-Ming Zhao, Xu Yan, Bao-Liang Lu |
| 2021 | ICONIP | EEG-Based Human Decision Confidence Measurement Using Graph Neural Networks. | Le-Dian Liu, Rui Li, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu |
| 2021 | ICONIP | A Cross-subject and Cross-modal Model for Multimodal Emotion Recognition. | Jian-Ming Zhang, Xu Yan, Ziyi Li, Li-Ming Zhao, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu |
| 2020 | ICASSP | Joint Semi-Supervised Feature Auto-Weighting and Classification Model for EEG-Based Cross-Subject Sleep Quality Evaluation. | Yong Peng, Qingxi Li, Wanzeng Kong, Jianhai Zhang, Bao-Liang Lu, Andrzej Cichocki |
| 2020 | IJCNN | Multimodal Emotion Recognition Using Deep Generalized Canonical Correlation Analysis with an Attention Mechanism. | Yu-Ting Lan, Wei Liu, Bao-Liang Lu |
| 2020 | IJCNN | Emotion Recognition under Sleep Deprivation Using a Multimodal Residual LSTM Network. | Le-Yan Tao, Bao-Liang Lu |
| 2019 | ICONIP | A Cross-Culture Study on Multimodal Emotion Recognition Using Deep Learning. | Lu Gan, Wei Liu, Yun Luo, Xun Wu, Bao-Liang Lu |
| 2019 | ICONIP | Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization. | Bo-Qun Ma, He Li, Wei-Long Zheng, Bao-Liang Lu |
| 2019 | IJCNN | Depersonalized Cross-Subject Vigilance Estimation with Adversarial Domain Generalization. | Bo-Qun Ma, He Li, Yun Luo, Bao-Liang Lu |
| 2019 | ISNN | A GAN-Based Data Augmentation Method for Multimodal Emotion Recognition. | Yun Luo, Lizhen Zhu, Bao-Liang Lu |
| 2018 | ICONIP | Driver Sleepiness Detection Using LSTM Neural Network. | Yini Deng, Yingying Jiao, Bao-Liang Lu |
| 2018 | ICONIP | Cross-Subject Emotion Recognition Using Deep Adaptation Networks. | He Li, Yiming Jin, Wei-Long Zheng, Bao-Liang Lu |
| 2018 | ICONIP | WGAN Domain Adaptation for EEG-Based Emotion Recognition. | Yun Luo, Si-Yang Zhang, Wei-Long Zheng, Bao-Liang Lu |
| 2018 | ICONIP | Multi-view Emotion Recognition Using Deep Canonical Correlation Analysis. | Jie-Lin Qiu, Wei Liu, Bao-Liang Lu |
| 2018 | ICONIP | Active Feedback Framework with Scan-Path Clustering for Deep Affective Models. | Li-Ming Zhao, Xin-Wei Li, Wei-Long Zheng, Bao-Liang Lu |
| 2018 | IJCNN | Multimodal Vigilance Estimation with Adversarial Domain Adaptation Networks. | He Li, Wei-Long Zheng, Bao-Liang Lu |
| 2018 | IJCNN | Sleep Quality Estimation with Adversarial Domain Adaptation: From Laboratory to Real Scenario. | Jia-Jun Tong, Yun Luo, Bo-Qun Ma, Wei-Long Zheng, Bao-Liang Lu, Xiao-Qi Song, Shi-Wei Ma |
| 2017 | ICONIP | Multimodal Emotion Recognition Using Deep Neural Networks. | Hao Tang, Wei Liu, Wei-Long Zheng, Bao-Liang Lu |
| 2017 | ICONIP | Identifying Gender Differences in Multimodal Emotion Recognition Using Bimodal Deep AutoEncoder. | Xue Yan, Wei-Long Zheng, Wei Liu, Bao-Liang Lu |
| 2017 | ICONIP | Investigating Gender Differences of Brain Areas in Emotion Recognition Using LSTM Neural Network. | Xue Yan, Wei-Long Zheng, Wei Liu, Bao-Liang Lu |
| 2017 | ICONIP | EEG-Based Sleep Quality Evaluation with Deep Transfer Learning. | Xing-Zan Zhang, Wei-Long Zheng, Bao-Liang Lu |
| 2017 | ICONIP | Emotion Annotation Using Hierarchical Aligned Cluster Analysis. | Wei-Ye Zhao, Sheng Fang, Ting Ji, Qian Ji, Wei-Long Zheng, Bao-Liang Lu |
| 2016 | AISTATS | On the Reducibility of Submodular Functions. | Jincheng Mei, Hao Zhang, Bao-Liang Lu |
| 2016 | COLING | Connecting Phrase based Statistical Machine Translation Adaptation. | Rui Wang, Hai Zhao, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita |
| 2016 | ICONIP | Emotion Recognition Using Multimodal Deep Learning. | Wei Liu, Wei-Long Zheng, Bao-Liang Lu |
| 2016 | ICONIP | Continuous Vigilance Estimation Using LSTM Neural Networks. | Nan Zhang, Wei-Long Zheng, Wei Liu, Bao-Liang Lu |
| 2016 | IJCAI | A Bilingual Graph-Based Semantic Model for Statistical Machine Translation. | Rui Wang, Hai Zhao, Sabine Ploux, Bao-Liang Lu, Masao Utiyama |
| 2016 | IJCAI | Personalizing EEG-Based Affective Models with Transfer Learning. | Wei-Long Zheng, Bao-Liang Lu |
| 2016 | IJCNN | Driving fatigue detection with fusion of EEG and forehead EOG. | Xue-Qin Huo, Wei-Long Zheng, Bao-Liang Lu |
| 2016 | IJCNN | Measuring sleep quality from EEG with machine learning approaches. | Li-Li Wang, Wei-Long Zheng, Hai-Wei Ma, Bao-Liang Lu |
| 2015 | AAAI | On Unconstrained Quasi-Submodular Function Optimization. | Jincheng Mei, Kang Zhao, Bao-Liang Lu |
| 2015 | ACII | Transfer components between subjects for EEG-based emotion recognition. | Wei-Long Zheng, Yong-Qi Zhang, Jia-Yi Zhu, Bao-Liang Lu |
| 2015 | ICONIP | Intensity-Depth Face Alignment Using Cascade Shape Regression. | Yang Cao, Bao-Liang Lu |
| 2015 | ICONIP | Transfer Components Between Subjects for EEG-based Driving Fatigue Detection. | Yong-Qi Zhang, Wei-Long Zheng, Bao-Liang Lu |
| 2015 | IJCAI | Combining Eye Movements and EEG to Enhance Emotion Recognition. | Yifei Lu, Wei-Long Zheng, Binbin Li, Bao-Liang Lu |
| 2015 | PACLIC | English to Chinese Translation: How Chinese Character Matters. | Rui Wang, Hai Zhao, Bao-Liang Lu |
| 2014 | EMNLP | Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation. | Rui Wang, Hai Zhao, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita |
| 2014 | ICONIP | Saliency Level Set Evolution. | Jincheng Mei, Bao-Liang Lu |
| 2014 | ICONIP | Online Object Tracking Based on Depth Image with Sparse Coding. | Shan-Chun Shen, Wei-Long Zheng, Bao-Liang Lu |
| 2014 | IJCNN | Recognizing slow eye movement for driver fatigue detection with machine learning approach. | Yingying Jiao, Yong Peng, Bao-Liang Lu, Xiaoping Chen, Shanguang Chen, Chunhui Wang |
| 2014 | IJCNN | EOG-based drowsiness detection using convolutional neural networks. | Xuemin Zhu, Wei-Long Zheng, Bao-Liang Lu, Xiaoping Chen, Shanguang Chen, Chunhui Wang |
| 2014 | IJCNN | EEG-based emotion recognition using discriminative graph regularized extreme learning machine. | Jia-Yi Zhu, Wei-Long Zheng, Yong Peng, Ruo-Nan Duan, Bao-Liang Lu |
| 2013 | CICLING | An Empirical Study on Word Segmentation for Chinese Machine Translation. | Hai Zhao, Masao Utiyama, Eiichiro Sumita, Bao-Liang Lu |
| 2013 | EMNLP | Converting Continuous-Space Language Models into N-Gram Language Models for Statistical Machine Translation. | Rui Wang, Masao Utiyama, Isao Goto, Eiichiro Sumita, Hai Zhao, Bao-Liang Lu |
| 2013 | ICONIP | Real-Time Head Detection with Kinect for Driving Fatigue Detection. | Yang Cao, Bao-Liang Lu |
| 2013 | ICONIP | Detection of Driving Fatigue Based on Grip Force on Steering Wheel with Wavelet Transformation and Support Vector Machine. | Fan Li, Xiao-Wei Wang, Bao-Liang Lu |
| 2013 | ICONIP | Marginalized Denoising Autoencoder via Graph Regularization for Domain Adaptation. | Yong Peng, Shen Wang, Bao-Liang Lu |
| 2013 | ICONIP | Structure Preserving Low-Rank Representation for Semi-supervised Face Recognition. | Yong Peng, Suhang Wang, Shen Wang, Bao-Liang Lu |
| 2013 | IJCNLP | Labeled Alignment for Recognizing Textual Entailment. | Xiaolin Wang, Hai Zhao, Bao-Liang Lu |
| 2012 | ICMLC | Automated quality assessment of web pages from textual content. | Xiaolin Wang, Hai Zhao, Bao-Liang Lu |
| 2012 | ICONIP | EEG-Based Emotion Recognition in Listening Music by Using Support Vector Machine and Linear Dynamic System. | Ruo-Nan Duan, Xiao-Wei Wang, Bao-Liang Lu |
| 2012 | ICONIP | Online Vigilance Analysis Combining Video and Electrooculography Features. | Ruofei Du, Ren-Jie Liu, Tian-Xiang Wu, Bao-Liang Lu |
| 2012 | ICONIP | EEG-Based Fatigue Classification by Using Parallel Hidden Markov Model and Pattern Classifier Combination. | Hui Sun, Bao-Liang Lu |
| 2012 | IJCNN | Parallel learning of large-scale multi-label classification problems with min-max modular LIBLINEAR. | Yangyang Chen, Bao-Liang Lu, Hai Zhao |
| 2012 | IJCNN | Online vigilance analysis based on electrooculography. | Zheng-Ping Wei, Bao-Liang Lu |
| 2012 | LREC | Spell Checking for Chinese. | Shaohua Yang, Hai Zhao, Xiaolin Wang, Bao-Liang Lu |
| 2012 | PACLIC | Towards a Semantic Annotation of English Television News - Building and Evaluating a Constraint Grammar FrameNet. | Shaohua Yang, Hai Zhao, Bao-Liang Lu |
| 2011 | CVPR | Time and space efficient spectral clustering via column sampling. | Mu Li, Xiao-Chen Lian, James T. Kwok, Bao-Liang Lu |
| 2011 | CVPR | Rank-SIFT: Learning to rank repeatable local interest points. | Bing Li, Rong Xiao, Zhiwei Li, Rui Cai, Bao-Liang Lu, Lei Zhang |
| 2011 | ICONIP | An Integrated Hierarchical Gaussian Mixture Model to Estimate Vigilance Level Based on EEG Recordings. | Jing-Nan Gu, Hongjun Liu, Hongtao Lu, Bao-Liang Lu |
| 2011 | ICONIP | A Sparse Common Spatial Pattern Algorithm for Brain-Computer Interface. | Li-Chen Shi, Yang Li, Rui-Hua Sun, Bao-Liang Lu |
| 2011 | ICONIP | EEG-Based Emotion Recognition Using Frequency Domain Features and Support Vector Machines. | Xiao-Wei Wang, Dan Nie, Bao-Liang Lu |
| 2011 | ICONIP | Removing Unrelated Features Based on Linear Dynamical System for Motor-Imagery-Based Brain-Computer Interface. | Jie Wu, Li-Chen Shi, Bao-Liang Lu |
| 2011 | IJCNLP | Enhance Top-down method with Meta-Classification for Very Large-scale Hierarchical Classification. | Xiaolin Wang, Hai Zhao, Bao-Liang Lu |
| 2010 | CoNLL | Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection. | Shaodian Zhang, Hai Zhao, Guodong Zhou, Bao-Liang Lu |
| 2010 | CVPR | Probabilistic models for supervised dictionary learning. | Xiao-Chen Lian, Zhiwei Li, Changhu Wang, Bao-Liang Lu, Lei Zhang |
| 2010 | CVPR | Online multiple instance learning with no regret. | Mu Li, James T. Kwok, Bao-Liang Lu |
| 2010 | ECCV | Max-Margin Dictionary Learning for Multiclass Image Categorization. | Xiao-Chen Lian, Zhiwei Li, Bao-Liang Lu, Lei Zhang |
| 2010 | ICISP | Selecting Optimal Orientations of Gabor Wavelet Filters for Facial Image Analysis. | Tianqi Zhang, Bao-Liang Lu |
| 2010 | ICML | Making Large-Scale Nystrm Approximation Possible. | Mu Li, James T. Kwok, Bao-Liang Lu |
| 2010 | ICMLC | A comparative study on two large-scale hierarchical text classification tasks' solutions. | Jian Zhang, Hai Zhao, Bao-Liang Lu |
| 2010 | ICONIP | Adaptive Ensemble Learning Strategy Using an Assistant Classifier for Large-Scale Imbalanced Patent Categorization. | Qi Kong, Hai Zhao, Bao-Liang Lu |
| 2010 | ICONIP | Age Classification Combining Contour and Texture Feature. | Yan-Ming Tang, Bao-Liang Lu |
| 2010 | ICONIP | Multi-view Gender Classification Using Hierarchical Classifiers Structure. | Tian-Xiang Wu, Bao-Liang Lu |
| 2010 | ISNN | Pruning Training Samples Using a Supervised Clustering Algorithm. | Minzhang Huang, Hai Zhao, Bao-Liang Lu |
| 2010 | SDM | Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm. | Wen-Yun Yang, James T. Kwok, Bao-Liang Lu |
| 2009 | ICONIP | Gender Classification Based on Support Vector Machine with Automatic Confidence. | Zheng Ji, Bao-Liang Lu |
| 2009 | IJCCI | Module Combination based on Decision Tree in Min-max Modular Network. | Yue Wang, Bao-Liang Lu, Zhi-Fei Ye |
| 2009 | ISNN | Incorporating Prior Knowledge into Task Decomposition for Large-Scale Patent Classification. | Chao Ma, Bao-Liang Lu, Masao Utiyama |
| 2009 | PACLIC | LogisticLDA: Regularizing Latent Dirichlet Allocation by Logistic Regression. | Jia-Cheng Guo, Bao-Liang Lu, Zhiwei Li, Lei Zhang |
| 2009 | PACLIC | Extracting Keyphrases from Chinese News Articles Using TextRank and Query Log Knowledge. | Weiming Liang, Changning Huang, Mu Li, Bao-Liang Lu |
| 2008 | APBC | Semantic Similarity Definition over Gene Ontology by Further Mining of the Information Content. | Yuan-Peng Li, Bao-Liang Lu |
| 2008 | APBC | String Kernels with Feature Selection for SVM Protein Classification. | Wen-Yun Yang, Bao-Liang Lu |
| 2008 | APBC | Classification of Protein Sequences Based on Word Segmentation Methods. | Yang Yang, Bao-Liang Lu, Wen-Yun Yang |
| 2008 | ICONIP | Gender Classification by Combining Facial and Hair Information. | Xiao-Chen Lian, Bao-Liang Lu |
| 2008 | IJCNLP | Cross Language Text Categorization Using a Bilingual Lexicon. | Ke Wu, Xiaolin Wang, Bao-Liang Lu |
| 2008 | IJCNN | Large-scale patent classification with min-max modular support vector machines. | Xiao-Lei Chu, Chao Ma, Jing Li, Bao-Liang Lu, Masao Utiyama, Hitoshi Isahara |
| 2008 | IJCNN | Multi-view gender classification based on local Gabor binary mapping pattern and support vector machines. | Bin Xia, He Sun, Bao-Liang Lu |
| 2007 | ICASSP | Person-Specific SIFT Features for Face Recognition. | Jun Luo, Yong Ma, Erina Takikawa, Shihong Lao, Masato Kawade, Bao-Liang Lu |
| 2007 | ICONIP | A Framework for Multi-view Gender Classification. | Jing Li, Bao-Liang Lu |
| 2007 | ICONIP | Incorporating Domain Knowledge into a Min-Max Modular Support Vector Machine for Protein Subcellular Localization. | Yang Yang, Bao-Liang Lu |
| 2007 | IJCNN | Semi-Supervised Clustering for Vigilance Analysis Based on EEG. | Li-Chen Shi, Hong Yu, Bao-Liang Lu |
| 2007 | IJCNN | Learning Imbalanced Data Sets with a Min-Max Modular Support Vector Machine. | Zhi-Fei Ye, Bao-Liang Lu |
| 2007 | IJCNN | Learning Concepts from Large-Scale Data Sets by Pairwise Coupling with Probabilistic Outputs. | Feng Zhou, Bao-Liang Lu |
| 2007 | ISNN | A Confident Majority Voting Strategy for Parallel and Modular Support Vector Machines. | Yimin Wen, Bao-Liang Lu |
| 2007 | ISNN | A Probabilistic Approach to Feature Selection for Multi-class Text Categorization. | Ke Wu, Bao-Liang Lu, Masao Uchiyama, Hitoshi Isahara |
| 2007 | PAKDD | Incremental Learning of Support Vector Machines by Classifier Combining. | Yimin Wen, Bao-Liang Lu |
| 2007 | PAKDD | Cross-Lingual Document Clustering. | Ke Wu, Bao-Liang Lu |
| 2006 | CIBCB | A Comparative Study on Feature Extraction from Protein Sequences for Subcellular Localization Prediction. | Wen-Yun Yang, Bao-Liang Lu, Yang Yang |
| 2006 | ICONIP | Fast Learning for Statistical Face Detection. | Zhi-Gang Fan, Bao-Liang Lu |
| 2006 | ICPR | A Hybrid Method of Unsupervised Feature Selection Based on Ranking. | Yun Li, Bao-Liang Lu, Zhong-Fu Wu |
| 2006 | IJCNN | Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers. | Ken Chen, Bao-Liang Lu, James T. Kwok |
| 2006 | IJCNN | A New Supervised Clustering Algorithm Based on Min-Max Modular Network with Gaussian-Zero-Crossing Functions. | Jing Li, Bao-Liang Lu |
| 2006 | ISNN | Multi-view Gender Classification Using Local Binary Patterns and Support Vector Machines. | Hui-Cheng Lian, Bao-Liang Lu |
| 2006 | ISNN | Gender Recognition Using a Min-Max Modular Support Vector Machine with Equal Clustering. | Jun Luo, Bao-Liang Lu |
| 2006 | ISNN | Prediction of Protein Subcellular Multi-locations with a Min-Max Modular Support Vector Machine. | Yang Yang, Bao-Liang Lu |
| 2006 | ISNN | A Modular Reduction Method for | Hai Zhao, Bao-Liang Lu |
| 2006 | PACLIC | Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling. | Hai Zhao, Changning Huang, Mu Li, Bao-Liang Lu |
| 2005 | CIBCB | Extracting Features from Protein Sequences Using Chinese Segmentation Techniques for Subcellular Localization. | Yang Yang, Bao-Liang Lu |
| 2005 | ICCV | Fast Recognition of Multi-View Faces with Feature Selection. | Zhi-Gang Fan, Bao-Liang Lu |
| 2005 | ICNC | Multi-view Face Recognition with Min-Max Modular SVMs. | Zhi-Gang Fan, Bao-Liang Lu |
| 2005 | ICNC | Gender Recognition Using a Min-Max Modular Support Vector Machine. | Hui-Cheng Lian, Bao-Liang Lu, Erina Takikawa, Satoshi Hosoi |
| 2005 | ICNC | An Algorithm for Pruning Redundant Modules in Min-Max Modular Network with GZC Function. | Jing Li, Bao-Liang Lu, Michinori Ichikawa |
| 2005 | ICNC | A General Procedure for Combining Binary Classifiers and Its Performance Analysis. | Hai Zhao, Bao-Liang Lu |
| 2005 | IJCNN | An algorithm for pruning redundant modules in min-ma modular network [min-ma read min-max]. | Hui-Cheng Lian, Bao-Liang Lu |
| 2005 | IJCNN | Fast text categorization with min-max modular support vector machines. | Feng-Yao Liu, Ke Wu, Hai Zhao, Bao-Liang Lu |
| 2005 | IJCNN | On efficient selection of binary classifiers for min-max modular classifier. | Hai Zhao, Bao-Liang Lu |
| 2005 | ISNN | Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function. | Jing Li, Bao-Liang Lu, Michinori Ichikawa |
| 2005 | ISNN | Task Decomposition Using Geometric Relation for Min-Max Modular SVMs. | Kai-An Wang, Hai Zhao, Bao-Liang Lu |
| 2005 | ISNN | A Hierarchical and Parallel Method for Training Support Vector Machines. | Yimin Wen, Bao-Liang Lu |
| 2005 | ISNN | Structure Pruning Strategies for Min-Max Modular Network. | Yang Yang, Bao-Liang Lu |
| 2005 | ISNN | Improvement on Response Performance of Min-Max Modular Classifier by Symmetric Module Selection. | Hai Zhao, Bao-Liang Lu |
| 2004 | CIS | A Modular k-Nearest Neighbor Classification Method for Massively Parallel Text Categorization. | Hai Zhao, Bao-Liang Lu |
| 2004 | ICONIP | Feature Selection for Fast Image Classification with Support Vector Machines. | Zhi-Gang Fan, Kai-An Wang, Bao-Liang Lu |
| 2004 | ICONIP | Fault Diagnosis for Industrial Images Using a Min-Max Modular Neural Network. | Bin Huang, Bao-Liang Lu |
| 2004 | IJCNN | A part-versus-part method for massively parallel training of support vector machines. | Bao-Liang Lu, Kai-An Wang, Masao Utiyama, Hitoshi Isahara |
| 2004 | ISNN | An Adjusted Gaussian Skin-Color Model Based on Principal Component Analysis. | Zhi-Gang Fan, Bao-Liang Lu |
| 2004 | ISNN | A Cascade Method for Reducing Training Time and the Number of Support Vectors. | Yimin Wen, Bao-Liang Lu |
| 2004 | ISNN | Analysis of Fault Tolerance of a Combining Classifier. | Hai Zhao, Bao-Liang Lu |
| 2001 | ICANN | Massively Parallel Classification of EEG Signals Using Min-Max Modular Neural Networks. | Bao-Liang Lu, Jonghan Shin, Michinori Ichikawa |
| 2001 | ICANN | On-Line Error Detection of Annotated Corpus Using Modular Neural Networks. | Qing Ma, Bao-Liang Lu, Masaki Murata, Michinori Ichikawa, Hitoshi Isahara |
| 2000 | IJCNN | Emergence of Learning: An Approach to Coping with NP-Complete Problems in Learning. | Bao-Liang Lu, Michinori Ichikawa |
| 1998 | ICONIP | Decomposition and Parallel Learning of Imbalanced Classification Problems by Min-Max Modular Neural Network. | Bao-Liang Lu, Masami Ito |
| 1997 | IWANN | Task Decomposition Based on Class Relations: A Modular Neural Network Architecture for Pattern Classification. | Bao-Liang Lu, Masami Ito |