Using GARCH-GRNN Model to Forecast Financial Time Series. - Weimin Li 001; Jianwei Liu 006; Jiajin Le (ISCIS, 2005)

Applications of AR*-GRNN model for financial time series forecasting. - Weimin Li 001; Yishu Luo; Qin Zhu; Jianwei Liu 006; Jiajin Le (Neural Comput. Appl., 2008)

Contrastive divergence learning for the Restricted Boltzmann Machine. - Jian-Wei Liu 006; Guang-Hui Chi; Xiong-Lin Luo (ICNC, 2013)

Iterative Reweighted Noninteger Norm Regularizing SVM for Gene Expression Data Classification. - Jianwei Liu 006; Shuang Cheng Li; Xionglin Luo (Comput. Math. Methods Medicine, 2013)

Output-Feedback and Inverse Optimal Control of a Class of Stochastic Nonlinear Systems with More General Growth Conditions. - Jianwei Liu 006; Longchuan Guo; Xin Zuo; Huaqing Liang (J. Appl. Math., 2013)

Design and stability analysis of networked control system with random delay and data dropout using a novel proactive strategy. - Yingyao Duan; Xin Zuo; Jianwei Liu 006 (ICCA, 2014)

Non-integer norm regularization SVM via Legendre-Fenchel duality. - Jian-Wei Liu 006; Yuan Liu (Neurocomputing, 2014)

Multiple source domain adaptation: A bound using p-norm covering numbers. - Jianwei Liu 006; Jiajia Zhou; Xionglin Luo (TAAI, 2015)

Multiple source domain adaptation: A sharper bound using weighted Rademacher complexity. - Jianwei Liu 006; Jiajia Zhou; Xionglin Luo (TAAI, 2015)

Rademacher complexity bound for domain adaptation regression. - Jiajia Zhou; Jianwei Liu 006; Xionglin Luo (TAAI, 2015)

概率图模型推理方法的研究进展 (Research and Development on Inference Technique in Probabilistic Graphical Models). - Jianwei Liu 006; Lipeng Cui; Haien Li; Xionglin Luo (计算机科学, 2015)

结构稀疏模型及其算法研究进展 (Research and Development on Structured Sparse Models and Algorithms). - Jian-Wei Liu 006; Lipeng Cui; Xionglin Luo (计算机科学, 2016)

Group variable selection and parameter estimation via Group Berhu method. - Jian-Wei Liu 006; Lipeng Cui; Xiong-Lin Luo (ICMLC, 2017)

The Influence Maximization Problem in the Network Under Node Personalized Characteristics. - Weimin Li 001; Jun Mo; Yue Liu; Nobuyasu Ito; Yohsuke Murase; Jianwei Liu 006 (DASC/PiCom/DataCom/CyberSciTech, 2018)

MRAC-MU Online Learning. - Si-Si Zhang; Jianwei Liu 006; Xin Zuo; Xin Wan; Mohamed S. Kamel (ICARCV, 2018)

Affine Transformation Capsule Net. - Runkun Lu; Jianwei Liu 006; Siming Lian; Xin Zuo (PAKDD (Workshops), 2018)

Rank Pruning Approach for Noisy Multi-label Learning. - Siming Lian; Jianwei Liu 006; Runkun Lu; Xionglin Luo (SMC, 2018)

Improved backstepping control for stochastic high-order nonlinear time delay system with a constructive mechanical system. - Long-Chuan Guo; Jian-Wei Liu 006 (Trans. Inst. Meas. Control, 2018)

Online Learning Algorithm Based on Adaptive Control Theory. - Jianwei Liu 006; Jiajia Zhou; Mohamed S. Kamel; Xiong-Lin Luo (IEEE Trans. Neural Networks Learn. Syst., 2018)

Multi-View Capsule Network. - Jianwei Liu 006; Xi-hao Ding; Runkun Lu; Yuanfeng Lian; Dianzhong Wang; Xionglin Luo (ICANN (1), 2019)

DDRM-CapsNet: Capsule Network Based on Deep Dynamic Routing Mechanism for Complex Data. - Jianwei Liu 006; Feng Gao; Runkun Lu; Yuanfeng Lian; Dianzhong Wang; Xionglin Luo; Chu-ran Wang (ICANN (1), 2019)

Phase Retrieval via Wirtinger Flow Algorithm and Its Variants. - Jianwei Liu 006; Zhi-Juan Cao; Jing Liu; Xiong-Lin Luo; Weimin Li 001; Nobuyasu Ito; Long-Chuan Guo (ICMLC, 2019)

Comments on "Finite-Time Analysis of the Multiarmed Bandit Problem". - Lu-Ning Zhang; Xin Zuo; Jianwei Liu 006; Weimin Li 001; Nobuyasu Ito (ICMLC, 2019)

FSC-CapsNet: Fractionally-Strided Convolutional Capsule Network for complex data. - Jianwei Liu 006; Feng Gao; Runkun Lu; Yuanfeng Lian; Dianzhong Wang; Xionglin Luo; Chu-ran Wang (IJCNN, 2019)

Auto-encoder Based Co-training Multi-view Representation Learning. - Runkun Lu; Jianwei Liu 006; Yuan-Fang Wang; Hao-jie Xie; Xin Zuo (PAKDD (3), 2019)

Captured multi-label relations via joint deep supervised autoencoder. - Siming Lian; Jianwei Liu 006; Runkun Lu; Xionglin Luo (Appl. Soft Comput., 2019)

Learning Disentangled Representations with Attentive Joint Variational Autoencoder. - Wen-tao Li; Jianwei Liu 006; Xiu-yan Chen; Xiong-Lin Luo (ICONIP (5), 2020)

Partially Disentangled Latent Relations for Multi-label Deep Learning. - Siming Lian; Jianwei Liu 006; Xiong-Lin Luo (ICONIP (2), 2020)

Deep Reinforcement Learning with Temporal-Awareness Network. - Ze-Yu Liu 011; Jian-Wei Liu 006; Weimin Li 001; Xin Zuo (ICONIP (2), 2020)

Multi-view Subspace Adaptive Learning via Autoencoder and Attention. - Jianwei Liu 006; Hao-jie Xie; Runkun Lu; Xiong-Lin Luo (ICONIP (2), 2020)

An Improved Latent Low Rank Representation for Automatic Subspace Clustering. - Ya-nan Han; Jianwei Liu 006; Xiong-Lin Luo (IJCAI, 2020)

Survival analysis of failures based on Hawkes process with Weibull base intensity. - Lu-Ning Zhang; Jian-Wei Liu 006; Xin Zuo (Eng. Appl. Artif. Intell., 2020)

Multi-view representation learning in multi-task scene. - Runkun Lu; Jianwei Liu 006; Siming Lian; Xin Zuo (Neural Comput. Appl., 2020)

Bilevel Online Deep Learning in Non-stationary Environment. - Ya-nan Han; Jian-wei Liu 006; Bing-biao Xiao; Xin-Tan Wang; Xionglin Luo (ICANN (2), 2021)

Learning Optimal Primary Capsules by Information Bottleneck. - Ming-fei Hu; Jian-wei Liu 006; Weimin Li 001 (ICANN (1), 2021)

Abstracting Inter-instance Relations and Inter-label Correlation Simultaneously for Sparse Multi-label. - Siming Lian; Jianwei Liu 006 (ICONIP (5), 2021)

Tri-Transformer Hawkes Process: Three Heads are Better Than One. - Zhi-yan Song; Jianwei Liu 006; Lu-ning Zhang; Ya-nan Han (ICONIP (1), 2021)

GSNESR: A Global Social Network Embedding Approach for Social Recommendation. - Bing-biao Xiao; Jian-wei Liu 006 (ICONIP (1), 2021)

Multi-view subspace clustering with consistent and view-specific latent factors and coefficient matrices. - Runkun Lu; Jian-wei Liu 006; Xin Zuo; Weimin Li 001 (IJCNN, 2021)

Heterogeneous Graph Gated Attention Network. - Shuai Ma; Jian-Wei Liu 006; Xin Zuo; Weimin Li 001 (IJCNN, 2021)

Universal Transformer Hawkes process. - Lu-Ning Zhang; Jian-Wei Liu 006; Zhi-Yan Song; Xin Zuo; Weimin Li 001; Ze-Yu Liu 011 (IJCNN, 2021)

Learning 3D-Craft Generation with Predictive Action Neural Network. - Ze-Yu Liu 011; Jian-Wei Liu 006; Xin Zuo; Weimin Li 001 (MMM (1), 2021)

Online deep learning based on auto-encoder. - Si-Si Zhang; Jianwei Liu 006; Xin Zuo; Runkun Lu; Siming Lian (Appl. Intell., 2021)

Adaptive online incremental learning for evolving data streams. - Si-Si Zhang; Jianwei Liu 006; Xin Zuo (Appl. Soft Comput., 2021)

Survival Analysis of the Compressor Station Based on Hawkes Process with Weibull Base Intensity. - Lu-ning Zhang; Jianwei Liu 006; Xin Zuo (CoRR, 2021)

Multi-scale iterative refinement network for RGB-D salient object detection. - Ze-Yu Liu 011; Jian-wei Liu 006; Xin Zuo; Ming-fei Hu (Eng. Appl. Artif. Intell., 2021)

Universal transformer Hawkes process with adaptive recursive iteration. - Lu-ning Zhang; Jian-wei Liu 006; Zhi-yan Song; Xin Zuo (Eng. Appl. Artif. Intell., 2021)

Attentive multi-view deep subspace clustering net. - Runkun Lu; Jianwei Liu 006; Xin Zuo (Neurocomputing, 2021)

Partially disentangled latent relations for multi-label deep learning. - Siming Lian; Jianwei Liu 006; Runkun Lu; Xionglin Luo (Neural Comput. Appl., 2021)

GMM discriminant analysis with noisy label for each class. - Jianwei Liu 006; Zheng-ping Ren; Runkun Lu; Xiong-Lin Luo (Neural Comput. Appl., 2021)

Multi-peak Graph-based Multi-instance Learning for Weakly Supervised Object Detection. - Ruyi Ji; Zeyu Liu 011; Libo Zhang 001; Jianwei Liu 006; Xin Zuo; Yanjun Wu; Chen Zhao; Haofeng Wang; Lin Yang (ACM Trans. Multim. Comput. Commun. Appl., 2021)

Continual Learning Based on Knowledge Distillation and Representation Learning. - Xiu-yan Chen; Jianwei Liu 006; Wen-tao Li (ICANN (4), 2022)

Ensemble of One-Class Classifiers Based on Multi-level Hidden Representations Abstracted from Convolutional Autoencoder for Anomaly Detection. - Xin-Tan Wang; Jianwei Liu 006 (ICANN (3), 2022)

Continual Learning by Task-Wise Shared Hidden Representation Alignment. - Xu-hui Zhan; Jianwei Liu 006; Ya-nan Han (ICANN (2), 2022)

Hawkes Process via Graph Contrastive Discriminant Representation Learning and Transformer Capturing Long-Term Dependencies. - Ze Cao; Jian-wei Liu 006; Zi-Hao Cheng (ICONIP (4), 2022)

Sequential Three-Way Rules Class-Overlap Under-Sampling Based on Fuzzy Hierarchical Subspace for Imbalanced Data. - Qi Dai; Jian-wei Liu 006; Jia-Peng Yang (ICONIP (4), 2022)

The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain. - Ming-hui Wang; Jian-wei Liu 006 (ICONIP (4), 2022)

Two-Stage Multilayer Perceptron Hawkes Process. - Xiang Xing; Jian-wei Liu 006; Zi-Hao Cheng (ICONIP (4), 2022)

Hypergraph Neural Network Hawkes Process. - Zi-Hao Cheng; Jian-Wei Liu 006; Ze Cao (IJCNN, 2022)

Instance-level and Class-level Contrastive Incremental Learning for Image Classification. - Jia-yi Han; Jian-wei Liu 006 (IJCNN, 2022)

Selecting Related Knowledge via Efficient Channel Attention for Online Continual Learning. - Ya-nan Han; Jianwei Liu 006 (IJCNN, 2022)

Learning Unsupervised Disentangled Capsule via Mutual Information. - Ming-fei Hu; Ze-Yu Liu 011; Jianwei Liu 006 (IJCNN, 2022)

An Online Recurring Concept Meta-learning For Evolving Streams. - Si-Si Zhang; Jian-Wei Liu 006 (IJCNN, 2022)

The Time-Sequence Prediction via Temporal and Contextual Contrastive Representation Learning. - Yang-yang Liu; Jian-Wei Liu 006 (PRICAI (1), 2022)

Multi-granularity relabeled under-sampling algorithm for imbalanced data. - Qi Dai; Jian-wei Liu 006; Yang Liu (Appl. Soft Comput., 2022)

Partially latent factors based multi-view subspace learning. - Runkun Lu; Jianwei Liu 006; Ze-Yu Liu 011; Jinzhong Chen (Comput. Intell., 2022)

Tri-transformer Hawkes process via dot-product attention operations with event type and temporal encoding. - Zhi-yan Song; Jian-wei Liu 006 (Comput. Intell., 2022)

Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity. - Jian-wei Liu 006; Xi-hao Ding; Runkun Lu; Xionglin Luo (CoRR, 2022)

Multi-View Non-negative Matrix Factorization Discriminant Learning via Cross Entropy Loss. - Jian-wei Liu 006; Yuan-Fang Wang; Runkun Lu; Xionglin Luo (CoRR, 2022)

Online Continual Learning via the Meta-learning update with Multi-scale Knowledge Distillation and Data Augmentation. - Ya-nan Han; Jianwei Liu 006 (Eng. Appl. Artif. Intell., 2022)

Class-imbalanced positive instances augmentation via three-line hybrid. - Qi Dai; Jian-wei Liu 006; Jia-Peng Yang (Knowl. Based Syst., 2022)

Multi-scale attentional similarity guidance network for few-shot semantic segmentation. - Ze-Yu Liu 011; Jian-wei Liu 006 (Neural Comput. Appl., 2022)

Kernel-based similarity sorting and allocation for few-shot semantic segmentation. - Ze-Yu Liu 011; Jian-wei Liu 006 (Neural Comput. Appl., 2022)

Temporal attention augmented transformer Hawkes process. - Lu-ning Zhang; Jian-wei Liu 006; Zhi-yan Song; Xin Zuo (Neural Comput. Appl., 2022)

Online continual learning via the knowledge invariant and spread-out properties. - Ya-nan Han; Jian-wei Liu 006 (Expert Syst. Appl., 2023)

Distance-based arranging oversampling technique for imbalanced data. - Qi Dai; Jian-wei Liu 006; Jia-Liang Zhao (Neural Comput. Appl., 2023)

β-CapsNet: learning disentangled representation for CapsNet by information bottleneck. - Ming-fei Hu; Jian-wei Liu 006 (Neural Comput. Appl., 2023)

Linear normalization attention neural Hawkes process. - Zhi-yan Song; Jian-wei Liu 006; Jie Yang 002; Lu-ning Zhang (Neural Comput. Appl., 2023)

Part-aware attention correctness for video salient object detection. - Ze-Yu Liu 011; Jian-Wei Liu 006 (Eng. Appl. Artif. Intell., 2023)

Self-supervised contrastive learning for heterogeneous graph based on multi-pretext tasks. - Shuai Ma; Jian-wei Liu 006 (Neural Comput. Appl., 2023)

Class-overlap undersampling based on Schur decomposition for Class-imbalance problems. - Qi Dai; Jianwei Liu 006; Yong-hui Shi (Expert Syst. Appl., 2023)

Hypergraph attentional convolutional neural network for salient object detection. - Zeyu Liu; Jian-wei Liu 006 (Vis. Comput., 2023)

Adaptively Sparse Transformers Hawkes Process. - Yue Gao; Jian-Wei Liu 006 (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2023)

More effective and efficient exploration via more refined gradient information. - Xiu-yan Chen; Jian-Wei Liu 006 (Appl. Intell., 2023)

An attempt to apply the homotopy method to the domain of machine learning. - Yang-yang Liu; Jian-wei Liu 006 (Expert Syst. Appl., 2023)

mcVAE: disentangling by mean constraint. - Ming-fei Hu; Ze-Yu Liu 011; Jian-wei Liu 006 (Vis. Comput., 2024)