| 2026 | AAAI | Adaptive and Asymptotic Mean-based Subclass Discriminant Analysis. | Yuzhe Feng, Yunlong Gao, Feiping Nie |
| 2026 | AAAI | S2-Boost: Synergistic Semantic Boosting for Coarse-to-Fine Ensemble Learning. | Guanxiong He, Zheng Wang, Jie Wang, Liaoyuan Tang, Rong Wang, Feiping Nie |
| 2026 | AAAI | Towards Federated Clustering: A Client-wise Private Graph Aggregation Framework. | Guanxiong He, Zheng Wang, Jie Wang, Liaoyuan Tang, Rong Wang, Feiping Nie |
| 2026 | AAAI | Reliable-View 2D-3D Key-Part Aligned Transformer with Reinforced Masking for 3D Point Cloud Understanding. | Xianglong Jin, Zheng Wang, Rong Wang, Feiping Nie |
| 2026 | ACL | OSCR-Attack: One-Shot Character Level Attacks through Self-Optimizing Continuous Relaxation. | Lingyi Kong, Zhuo Liu, Zhanghao Hu, Qilong Qiu, Yutao Yang, Jingjing Xue, Zheng Wang, Lin Gui, Feiping Nie |
| 2026 | ICDE | FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis. | Da Zhang, Bingyu Li, Zhiyuan Zhao, Feiping Nie, Junyu Gao, Xuelong Li |
| 2025 | AAAI | Language Pre-training Guided Masking Representation Learning for Time Series Classification. | Liaoyuan Tang, Zheng Wang, Jie Wang, Guanxiong He, Zhezheng Hao, Rong Wang, Feiping Nie |
| 2025 | CIKM | Point-DMAE: Point Cloud Self-supervised Learning via Density-directed Masked Autoencoders. | Xianglong Jin, Zheng Wang, Wenjie Zheng, Feiping Nie |
| 2025 | ICASSP | Efficient Co-clustering via Anchor-refined Label Spreading. | Fangyuan Xie, Feiping Nie, Weizhong Yu, Xuelong Li |
| 2025 | ICASSP | Efficient Anchor Graph Clustering Through Enhanced Within-Cluster Homogeneity. | Fangyuan Xie, Lin Zhao, Jingjing Xue, Feiping Nie, Weizhong Yu, Xuelong Li |
| 2025 | ICASSP | A Margin-Maximizing Fine-Grained Ensemble Method. | Jinghui Yuan, Hao Chen, Renwei Luo, Feiping Nie |
| 2025 | ICDM | High-Quality Label Learning in Generalized Category Discovery. | Yu Duan, Junzhi He, Feiping Nie, Quanxue Gao, Cheng Deng |
| 2025 | IJCAI | Capturing Individuality and Commonality Between Anchor Graphs for Multi-View Clustering. | Zhoumin Lu, Yongbo Yu, Linru Ma, Feiping Nie, Rong Wang |
| 2024 | AAAI | Multi-Class Support Vector Machine with Maximizing Minimum Margin. | Feiping Nie, Zhezheng Hao, Rong Wang |
| 2024 | ICASSP | Discriminative Semi-Supervised Feature Selection Via a Class-Credible Pseudo-Label Learning Framework. | Xin Qi, Han Zhang, Feiping Nie |
| 2024 | ICASSP | Outlier-Robust Feature Selection with ℓ2, 1-Norm Minimization and Group Row-Sparsity Induced Constraints. | Jie Wang, Zheng Wang, Rong Wang, Feiping Nie, Xuelong Li |
| 2024 | ICASSP | Multi-View Subspace Clustering With Consensus Graph Contrastive Learning. | Jie Zhang, Yuan Sun, Yu Guo, Zheng Wang, Feiping Nie, Fei Wang |
| 2024 | ICLR | Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View. | Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu |
| 2024 | IJCAI | Perturbation Guiding Contrastive Representation Learning for Time Series Anomaly Detection. | Liaoyuan Tang, Zheng Wang, Guanxiong He, Rong Wang, Feiping Nie |
| 2024 | WWW | Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving. | Zhezheng Hao, Haonan Xin, Long Wei, Liaoyuan Tang, Rong Wang, Feiping Nie |
| 2024 | WWW | Simple Multigraph Convolution Networks. | Danyang Wu, Xinjie Shen, Jitao Lu, Jin Xu, Feiping Nie |
| 2023 | AAAI | Efficient Top-K Feature Selection Using Coordinate Descent Method. | Lei Xu, Rong Wang, Feiping Nie, Xuelong Li |
| 2023 | ICASSP | Multi-View K-Means with Laplacian Embedding. | Zhezheng Hao, Zhoumin Lu, Feiping Nie, Rong Wang, Xuelong Li |
| 2023 | ICASSP | Unsupervised Feature Selection with self-Weighted and ℓ2,0-Norm Constraint. | Yongjin Yuan, Zheng Wang, Feiping Nie, Xuelong Li |
| 2023 | ICASSP | Multilayer Subspace Learning With Self-Sparse Robustness for Two-Dimensional Feature Extraction. | Han Zhang, Maoguo Gong, Feiping Nie, Xuelong Li |
| 2022 | CIKM | Scalable Multiple Kernel | Yihang Lu, Haonan Xin, Rong Wang, Feiping Nie, Xuelong Li |
| 2022 | CIKM | Self-Paced and Discrete Multiple Kernel | Yihang Lu, Xuan Zheng, Jitao Lu, Rong Wang, Feiping Nie, Xuelong Li |
| 2022 | ICASSP | Discrete Multi-Kernel K-Means with Diverse and Optimal Kernel Learning. | Yihang Lu, Jitao Lu, Rong Wang, Feiping Nie |
| 2022 | ICASSP | Multiple Kernel K-Means Clustering with Simultaneous Spectral Rotation. | Jitao Lu, Yihang Lu, Rong Wang, Feiping Nie, Xuelong Li |
| 2022 | ICPR | A Unified Framework for Discrete Multi-kernel k-means with Kernel Diversity Regularization. | Yihang Lu, Xuan Zheng, Rong Wang, Feiping Nie, Xuelong Li |
| 2022 | IJCAI | EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion. | Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan |
| 2021 | AAAI | Fast Multi-view Discrete Clustering with Anchor Graphs. | Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie |
| 2021 | AAAI | Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations. | Hoon Seo, Lodewijk Brand, Hua Wang, Feiping Nie |
| 2021 | CIKM | New Tight Relaxations of Rank Minimization for Multi-Task Learning. | Wei Chang, Feiping Nie, Rong Wang, Xuelong Li |
| 2021 | ICASSP | Adaptive Feature Weight Learning For Robust Clustering Problem with Sparse Constraint. | Feiping Nie, Wei Chang, Xuelong Li, Jin Xu, Gongfu Li |
| 2021 | ICASSP | Dependence-Guided Multi-View Clustering. | Xia Dong, Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li |
| 2021 | ICASSP | A Rank-Constrained Clustering Algorithm with Adaptive Embedding. | Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li |
| 2021 | ICASSP | Multi-Task Learning Via Sharing Inexact Low-Rank Subspace. | Xiaoqian Wang, Feiping Nie |
| 2021 | ICASSP | Fast Local Representation Learning with Adaptive Anchor Graph. | Canyu Zhang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li |
| 2021 | IJCAI | Discrete Multiple Kernel k-means. | Rong Wang, Jitao Lu, Yihang Lu, Feiping Nie, Xuelong Li |
| 2021 | IJCAI | GSPL: A Succinct Kernel Model for Group-Sparse Projections Learning of Multiview Data. | Danyang Wu, Jin Xu, Xia Dong, Meng Liao, Rong Wang, Feiping Nie, Xuelong Li |
| 2021 | WISE | NP-PROV: Neural Processes with Position-Relevant-Only Variances. | Xuesong Wang, Lina Yao, Xianzhi Wang, Feiping Nie, Boualem Benatallah |
| 2020 | APWEB | Unsupervised Deep Hashing with Structured Similarity Learning. | Xuanrong Pang, Xiaojun Chen, Shu Yang, Feiping Nie |
| 2020 | CVPR | Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers. | Lyujian Lu, Hua Wang, Saad Elbeleidy, Feiping Nie |
| 2020 | ICA3PP | Clustering by Unified Principal Component Analysis and Fuzzy C-Means with Sparsity Constraint. | Jikui Wang, Quanfu Shi, Zhengguo Yang, Feiping Nie |
| 2020 | ICASSP | Fast Clustering With Co-Clustering Via Discrete Non-Negative Matrix Factorization for Image Identification. | Feiping Nie, Shenfei Pei, Rong Wang, Xuelong Li |
| 2020 | ICASSP | Revisiting Fast Spectral Clustering with Anchor Graph. | Cheng-Long Wang, Feiping Nie, Rong Wang, Xuelong Li |
| 2020 | ICASSP | Multi-View Clustering Via Mixed Embedding Approximation. | Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li |
| 2020 | ICONIP | A Factorized Extreme Learning Machine and Its Applications in EEG-Based Emotion Recognition. | Yong Peng, Rixin Tang, Wanzeng Kong, Feiping Nie |
| 2020 | IJCAI | Semi-supervised Clustering via Pairwise Constrained Optimal Graph. | Feiping Nie, Han Zhang, Rong Wang, Xuelong Li |
| 2020 | IJCAI | Discriminative Feature Selection via A Structured Sparse Subspace Learning Module. | Zheng Wang, Feiping Nie, Lai Tian, Rong Wang, Xuelong Li |
| 2019 | AAAI | A Probabilistic Derivation of LASSO and L12-Norm Feature Selections. | Di Ming, Chris Ding, Feiping Nie |
| 2019 | AAAI | Semi-Supervised Feature Selection with Adaptive Discriminant Analysis. | Weichan Zhong, Xiaojun Chen, Guowen Yuan, Yiqin Li, Feiping Nie |
| 2019 | AISTATS | A Unified Weight Learning Paradigm for Multi-view Learning. | Lai Tian, Feiping Nie, Xuelong Li |
| 2019 | CVPR | Listen to the Image. | Di Hu, Dong Wang, Xuelong Li, Feiping Nie, Qi Wang |
| 2019 | CVPR | Deep Multimodal Clustering for Unsupervised Audiovisual Learning. | Di Hu, Feiping Nie, Xuelong Li |
| 2019 | ICASSP | Robust Subspace Clustering by Learning an Optimal Structured Bipartite Graph via Low-rank Representation. | Wei Chang, Feiping Nie, Rong Wang, Xuelong Li |
| 2019 | ICASSP | Dense Multimodal Fusion for Hierarchically Joint Representation. | Di Hu, Chengze Wang, Feiping Nie, Xuelong Li |
| 2019 | ICASSP | Flexible Non-negative Matrix Factorization with Adaptively Learned Graph Regularization. | Yong Peng, Yanfang Long, Feiwei Qin, Wanzeng Kong, Feiping Nie, Andrzej Cichocki |
| 2019 | ICASSP | Joint Structured Graph Learning and Clustering Based on Concept Factorization. | Yong Peng, Rixin Tang, Wanzeng Kong, Jianhai Zhang, Feiping Nie, Andrzej Cichocki |
| 2019 | ICASSP | Joint Structured Graph Learning and Unsupervised Feature Selection. | Yong Peng, Leijie Zhang, Wanzeng Kong, Feiping Nie, Andrzej Cichocki |
| 2019 | ICASSP | Unsupervised Feature Selection Based on Reconstruction Error Minimization. | Sheng Yang, Rui Zhang, Feiping Nie, Xuelong Li |
| 2019 | IJCAI | Worst-Case Discriminative Feature Selection. | Shuangli Liao, Quanxue Gao, Feiping Nie, Yang Liu, Xiangdong Zhang |
| 2019 | IJCAI | Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances. | Kai Liu, Lodewijk Brand, Hua Wang, Feiping Nie |
| 2019 | IJCAI | Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method. | Haoxuan Yang, Kai Liu, Hua Wang, Feiping Nie |
| 2019 | KDD | K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters. | Feiping Nie, Cheng-Long Wang, Xuelong Li |
| 2019 | MICCAI | Joint Identification of Network Hub Nodes by Multivariate Graph Inference. | Defu Yang, Chenggang Yan, Feiping Nie, Xiaofeng Zhu, Md Asadullah Turja, Leo Charles Peek Zsembik, Martin Styner, Guorong Wu |
| 2018 | AAAI | Balanced Clustering via Exclusive Lasso: A Pragmatic Approach. | Zhihui Li, Feiping Nie, Xiaojun Chang, Zhigang Ma, Yi Yang |
| 2018 | AAAI | Multi-Rate Gated Recurrent Convolutional Networks for Video-Based Pedestrian Re-Identification. | Zhihui Li, Lina Yao, Feiping Nie, Dingwen Zhang, Min Xu |
| 2018 | AAAI | New l | Xu Yang, Cheng Deng, Xianglong Liu, Feiping Nie |
| 2018 | AAAI | Discriminative Semi-Supervised Feature Selection via Rescaled Least Squares Regression-Supplement. | Guowen Yuan, Xiaojun Chen, Chen Wang, Feiping Nie, Liping Jing |
| 2018 | CIKM | Embedding Fuzzy K-Means with Nonnegative Spectral Clustering via Incorporating Side Information. | Muhan Guo, Rui Zhang, Feiping Nie, Xuelong Li |
| 2018 | CVPR | Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances. | Kai Liu, Hua Wang, Feiping Nie, Hao Zhang |
| 2018 | ICASSP | Directly Solving the Original Ratiocut Problem for Effective Data Clustering. | Jing Li, Feiping Nie, Xuelong Li |
| 2018 | ICASSP | Parallel Vector Field Regularized Non-Negative Matrix Factorization for Image Representation. | Yong Peng, Rixin Tang, Wanzeng Kong, Feiwei Qin, Feiping Nie |
| 2018 | ICASSP | A Generalized Uncorrelated Ridge Regression with Nonnegative Labels for Unsupervised Feature Selection. | Han Zhang, Rui Zhang, Feiping Nie, Xuelong Li |
| 2018 | ICIP | Feature Selection via Incorporating Stiefel Manifold in Relaxed K-Means. | Guohao Cai, Rui Zhang, Feiping Nie, Xuelong Li |
| 2018 | ICIP | Self-Weighted Adaptive Locality Discriminant Analysis. | Muhan Guo, Feiping Nie, Xuelong Li |
| 2018 | ICIP | Locality-Based Discriminant Feature Selection with Trace Ratio. | Muhan Guo, Sheng Yang, Feiping Nie, Xuelong Li |
| 2018 | ICIP | Robust Low Rank Approxiamtion via Inliers Selection. | Zhanxuan Hu, Feiping Nie, Xuelong Li |
| 2018 | ICIP | Unsupervised Feature Selection with Local Structure Learning. | Sheng Yang, Feiping Nie, Xuelong Li |
| 2018 | KDD | Spectral Clustering of Large-scale Data by Directly Solving Normalized Cut. | Xiaojun Chen, Weijun Hong, Feiping Nie, Dan He, Min Yang, Joshua Zhexue Huang |
| 2018 | KDD | Calibrated Multi-Task Learning. | Feiping Nie, Zhanxuan Hu, Xuelong Li |
| 2018 | KDD | Multiview Clustering via Adaptively Weighted Procrustes. | Feiping Nie, Lai Tian, Xuelong Li |
| 2017 | AAAI | Local Centroids Structured Non-Negative Matrix Factorization. | Hongchang Gao, Feiping Nie, Heng Huang |
| 2017 | AAAI | Bilateral k-Means Algorithm for Fast Co-Clustering. | Junwei Han, Kun Song, Feiping Nie, Xuelong Li |
| 2017 | AAAI | A Multiview-Based Parameter Free Framework for Group Detection. | Xuelong Li, Mulin Chen, Feiping Nie, Qi Wang |
| 2017 | AAAI | Large Graph Hashing with Spectral Rotation. | Xuelong Li, Di Hu, Feiping Nie |
| 2017 | AAAI | Semi-Supervised Classifications via Elastic and Robust Embedding. | Yun Liu, Yiming Guo, Hua Wang, Feiping Nie, Heng Huang |
| 2017 | AAAI | Balanced Clustering with Least Square Regression. | Hanyang Liu, Junwei Han, Feiping Nie, Xuelong Li |
| 2017 | AAAI | Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling. | Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng |
| 2017 | AAAI | Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours. | Feiping Nie, Guohao Cai, Xuelong Li |
| 2017 | AAAI | Multiclass Capped ℓp-Norm SVM for Robust Classifications. | Feiping Nie, Xiaoqian Wang, Heng Huang |
| 2017 | AAAI | Unsupervised Large Graph Embedding. | Feiping Nie, Wei Zhu, Xuelong Li |
| 2017 | AAAI | Parameter Free Large Margin Nearest Neighbor for Distance Metric Learning. | Kun Song, Feiping Nie, Junwei Han, Xuelong Li |
| 2017 | AAAI | Multi-View Correlated Feature Learning by Uncovering Shared Component. | Xiaowei Xue, Feiping Nie, Sen Wang, Xiaojun Chang, Bela Stantic, Min Yao |
| 2017 | ICASSP | Embedded clustering via robust orthogonal least square discriminant analysis. | Rui Zhang, Feiping Nie, Xuelong Li |
| 2017 | ICASSP | Semi-supervised classification via both label and side information. | Rui Zhang, Feiping Nie, Xuelong Li |
| 2017 | ICASSP | Auto-weighted two-dimensional principal component analysis with robust outliers. | Rui Zhang, Feiping Nie, Xuelong Li |
| 2017 | ICASSP | Largest center-specific margin for dimension reduction. | Jian'an Zhang, Yuan Yuan, Feiping Nie, Qi Wang |
| 2017 | ICASSP | Fast Spectral Clustering with efficient large graph construction. | Wei Zhu, Feiping Nie, Xuelong Li |
| 2017 | ICCV | A Self-Balanced Min-Cut Algorithm for Image Clustering. | Xiaojun Chen, Joshua Zhexue Huang, Feiping Nie, Renjie Chen, Qingyao Wu |
| 2017 | IJCAI | Scalable Normalized Cut with Improved Spectral Rotation. | Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang, Min Yang |
| 2017 | IJCAI | Semi-supervised Feature Selection via Rescaled Linear Regression. | Xiaojun Chen, Guowen Yuan, Feiping Nie, Joshua Zhexue Huang |
| 2017 | IJCAI | Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering. | Junwei Han, Kai Xiong, Feiping Nie |
| 2017 | IJCAI | Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning. | Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu-Lai Chung, Heng Huang |
| 2017 | IJCAI | Locality Adaptive Discriminant Analysis. | Xuelong Li, Mulin Chen, Feiping Nie, Qi Wang |
| 2017 | IJCAI | Semi-supervised Orthogonal Graph Embedding with Recursive Projections. | Hanyang Liu, Junwei Han, Feiping Nie |
| 2017 | IJCAI | Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression. | Minnan Luo, Lingling Zhang, Feiping Nie, Xiaojun Chang, Buyue Qian, Qinghua Zheng |
| 2017 | IJCAI | Joint Capped Norms Minimization for Robust Matrix Recovery. | Feiping Nie, Zhouyuan Huo, Heng Huang |
| 2017 | IJCAI | Self-weighted Multiview Clustering with Multiple Graphs. | Feiping Nie, Jing Li, Xuelong Li |
| 2017 | IJCAI | Flexible Orthogonal Neighborhood Preserving Embedding. | Tianji Pang, Feiping Nie, Junwei Han |
| 2017 | IJCAI | Two dimensional Large Margin Nearest Neighbor for Matrix Classification. | Kun Song, Feiping Nie, Junwei Han |
| 2017 | IJCAI | Angle Principal Component Analysis. | Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie |
| 2017 | IJCAI | Convolutional 2D LDA for Nonlinear Dimensionality Reduction. | Qi Wang, Zequn Qin, Feiping Nie, Yuan Yuan |
| 2017 | IJCAI | Linear Manifold Regularization with Adaptive Graph for Semi-supervised Dimensionality Reduction. | Kai Xiong, Feiping Nie, Junwei Han |
| 2017 | IJCAI | Multi-view Feature Learning with Discriminative Regularization. | Jinglin Xu, Junwei Han, Feiping Nie |
| 2017 | IJCAI | Multi-Class Support Vector Machine via Maximizing Multi-Class Margins. | Jie Xu, Xianglong Liu, Zhouyuan Huo, Cheng Deng, Feiping Nie, Heng Huang |
| 2017 | IJCAI | Feature Selection via Scaling Factor Integrated Multi-Class Support Vector Machines. | Jinglin Xu, Feiping Nie, Junwei Han |
| 2017 | IJCNN | Projected clustering via robust orthogonal least square regression with optimal scaling. | Rui Zhang, Feiping Nie, Xuelong Li |
| 2016 | AAAI | Graph-without-cut: An Ideal Graph Learning for Image Segmentation. | Lianli Gao, Jingkuan Song, Feiping Nie, Fuhao Zou, Nicu Sebe, Heng Tao Shen |
| 2016 | AAAI | Discriminative Vanishing Component Analysis. | Chenping Hou, Feiping Nie, Dacheng Tao |
| 2016 | AAAI | New l1-Norm Relaxations and Optimizations for Graph Clustering. | Feiping Nie, Hua Wang, Cheng Deng, Xinbo Gao, Xuelong Li, Heng Huang |
| 2016 | AAAI | The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. | Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang |
| 2016 | AAAI | Unsupervised Feature Selection with Structured Graph Optimization. | Feiping Nie, Wei Zhu, Xuelong Li |
| 2016 | BMVC | Projective Unsupervised Flexible Embedding with Optimal Graph. | Wei Wang, Yan Yan, Feiping Nie, Xavier Alameda-Pineda, Shuicheng Yan, Nicu Sebe |
| 2016 | CVPR | Object Co-segmentation via Graph Optimized-Flexible Manifold Ranking. | Rong Quan, Junwei Han, Dingwen Zhang, Feiping Nie |
| 2016 | CVPR | Discriminatively Embedded K-Means for Multi-view Clustering. | Jinglin Xu, Junwei Han, Feiping Nie |
| 2016 | ICDM | Semi-Supervised Multi-label Dimensionality Reduction. | Baolin Guo, Chenping Hou, Feiping Nie, Dongyun Yi |
| 2016 | ICDM | Learning Task Relational Structure for Multi-task Feature Learning. | De Wang, Feiping Nie, Heng Huang |
| 2016 | ICPR | Unsupervised automatic attribute discovery method via multi-graph clustering. | Liangchen Liu, Feiping Nie, Teng Zhang, Arnold Wiliem, Brian C. Lovell |
| 2016 | IJCAI | Avoiding Optimal Mean Robust PCA/2DPCA with Non-greedy ℓ | Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng |
| 2016 | IJCAI | Subspace Clustering via New Low-Rank Model with Discrete Group Structure Constraint. | Feiping Nie, Heng Huang |
| 2016 | IJCAI | Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification. | Feiping Nie, Jing Li, Xuelong Li |
| 2016 | IJCAI | Fast Robust Non-Negative Matrix Factorization for Large-Scale Human Action Data Clustering. | De Wang, Feiping Nie, Heng Huang |
| 2016 | IJCAI | Robust and Sparse Fuzzy K-Means Clustering. | Jinglin Xu, Junwei Han, Kai Xiong, Feiping Nie |
| 2016 | ICPR | Unsupervised feature extraction using a learned graph with clustering structure. | Wenzhang Zhuge, Chenping Hou, Feiping Nie, Dongyun Yi |
| 2016 | ICTAI | A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification. | Shuai Zheng, Feiping Nie, Chris H. Q. Ding, Heng Huang |
| 2016 | KDD | Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm. | Zhouyuan Huo, Feiping Nie, Heng Huang |
| 2016 | KDD | Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. | Xiaoqian Wang, Feiping Nie, Heng Huang |
| 2016 | MICCAI | Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease. | Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu |
| 2015 | AAAI | A Convex Formulation for Spectral Shrunk Clustering. | Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang, Xiaofang Zhou |
| 2015 | AAAI | Large-Scale Multi-View Spectral Clustering via Bipartite Graph. | Yeqing Li, Feiping Nie, Heng Huang, Junzhou Huang |
| 2015 | AAAI | Learning Robust Locality Preserving Projection via p-Order Minimization. | Hua Wang, Feiping Nie, Heng Huang |
| 2015 | AAAI | A Closed Form Solution to Multi-View Low-Rank Regression. | Shuai Zheng, Xiao Cai, Chris H. Q. Ding, Feiping Nie, Heng Huang |
| 2015 | CIKM | Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF. | Hongchang Gao, Feiping Nie, Tom Weidong Cai, Heng Huang |
| 2015 | CVPR | Optimal graph learning with partial tags and multiple features for image and video annotation. | Lianli Gao, Jingkuan Song, Feiping Nie, Yan Yan, Nicu Sebe, Heng Tao Shen |
| 2015 | ICCV | Multi-view Subspace Clustering. | Hongchang Gao, Feiping Nie, Xuelong Li, Heng Huang |
| 2015 | IJCAI | A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering. | Jin Huang, Feiping Nie, Heng Huang |
| 2015 | IJCAI | Robust Dictionary Learning with Capped l1-Norm. | Wenhao Jiang, Feiping Nie, Heng Huang |
| 2015 | IJCAI | Discriminative Unsupervised Dimensionality Reduction. | Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang |
| 2015 | MICCAI | Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. | Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaqun Goi Cortes, Yang Wang, Feiping Nie, John D. West, Andrew J. Saykin, Li Shen, Heng Huang |
| 2014 | AAAI | A Convex Formulation for Semi-Supervised Multi-Label Feature Selection. | Xiaojun Chang, Feiping Nie, Yi Yang, Heng Huang |
| 2014 | AAAI | Globally and Locally Consistent Unsupervised Projection. | Hua Wang, Feiping Nie, Heng Huang |
| 2014 | AAAI | Low-Rank Tensor Completion with Spatio-Temporal Consistency. | Hua Wang, Feiping Nie, Heng Huang |
| 2014 | AAAI | Feature Selection at the Discrete Limit. | Miao Zhang, Chris H. Q. Ding, Ya Zhang, Feiping Nie |
| 2014 | ICML | Linear Time Solver for Primal SVM. | Feiping Nie, Yizhen Huang, Heng Huang |
| 2014 | ICML | Optimal Mean Robust Principal Component Analysis. | Feiping Nie, Jianjun Yuan, Heng Huang |
| 2014 | ICML | Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization. | Hua Wang, Feiping Nie, Heng Huang |
| 2014 | KDD | Clustering and projected clustering with adaptive neighbors. | Feiping Nie, Xiaoqian Wang, Heng Huang |
| 2014 | KDD | Large-scale adaptive semi-supervised learning via unified inductive and transductive model. | De Wang, Feiping Nie, Heng Huang |
| 2014 | MICCAI | Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model. | De Wang, Yang Wang, Feiping Nie, Jingwen Yan, Tom Weidong Cai, Andrew J. Saykin, Li Shen, Heng Huang |
| 2013 | AAAI | Robust Discrete Matrix Completion. | Jin Huang, Feiping Nie, Heng Huang |
| 2013 | AAAI | Spectral Rotation versus K-Means in Spectral Clustering. | Jin Huang, Feiping Nie, Heng Huang |
| 2013 | AAAI | Supervised and Projected Sparse Coding for Image Classification. | Jin Huang, Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2013 | CVPR | Heterogeneous Visual Features Fusion via Sparse Multimodal Machine. | Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2013 | ICCV | New Graph Structured Sparsity Model for Multi-label Image Annotations. | Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang |
| 2013 | ICCV | Heterogeneous Image Features Integration via Multi-modal Semi-supervised Learning Model. | Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang |
| 2013 | ICCV | Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization. | Hua Wang, Feiping Nie, Weidong Cai, Heng Huang |
| 2013 | ICML | Robust and Discriminative Self-Taught Learning. | Hua Wang, Feiping Nie, Heng Huang |
| 2013 | ICML | Multi-View Clustering and Feature Learning via Structured Sparsity. | Hua Wang, Feiping Nie, Heng Huang |
| 2013 | IJCAI | Exact Top-k Feature Selection via l2, 0-Norm Constraint. | Xiao Cai, Feiping Nie, Heng Huang |
| 2013 | IJCAI | Multi-View K-Means Clustering on Big Data. | Xiao Cai, Feiping Nie, Heng Huang |
| 2013 | IJCAI | Social Trust Prediction Using Rank-k Matrix Recovery. | Jin Huang, Feiping Nie, Heng Huang, Yu Lei, Chris H. Q. Ding |
| 2013 | IJCAI | Thinking of Images as What They Are: Compound Matrix Regression for Image Classification. | Zhigang Ma, Yi Yang, Feiping Nie, Nicu Sebe |
| 2013 | IJCAI | Adaptive Loss Minimization for Semi-Supervised Elastic Embedding. | Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding |
| 2013 | IJCAI | Early Active Learning via Robust Representation and Structured Sparsity. | Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding |
| 2013 | KDD | On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions. | Xiao Cai, Chris H. Q. Ding, Feiping Nie, Heng Huang |
| 2013 | MICCAI | A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis. | Heng Huang, Jingwen Yan, Feiping Nie, Jin Huang, Weidong Cai, Andrew J. Saykin, Li Shen |
| 2013 | MICCAI | Minimizing Joint Risk of Mislabeling for Iterative Patch-Based Label Fusion. | Guorong Wu, Qian Wang, Shu Liao, Daoqiang Zhang, Feiping Nie, Dinggang Shen |
| 2012 | AAAI | Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization. | Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2012 | CIKM | Trust prediction via aggregating heterogeneous social networks. | Jin Huang, Feiping Nie, Heng Huang, Yi-Cheng Tu |
| 2012 | CVPR | Robust and discriminative distance for Multi-Instance Learning. | Hua Wang, Feiping Nie, Heng Huang |
| 2012 | ICDM | Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization. | Feiping Nie, Hua Wang, Xiao Cai, Heng Huang, Chris H. Q. Ding |
| 2012 | ICML | An Iterative Locally Linear Embedding Algorithm. | Deguang Kong, Chris H. Q. Ding, Heng Huang, Feiping Nie |
| 2012 | MICCAI | Group-Wise Consistent Parcellation of Gyri via Adaptive Multi-view Spectral Clustering of Fiber Shapes. | Hanbo Chen, Xiao Cai, Dajiang Zhu, Feiping Nie, Tianming Liu, Heng Huang |
| 2012 | RECOMB | Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. | Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie |
| 2011 | AAAI | Learning Instance Specific Distance for Multi-Instance Classification. | Hua Wang, Feiping Nie, Heng Huang |
| 2011 | AAAI | Nonnegative Spectral Clustering with Discriminative Regularization. | Yi Yang, Heng Tao Shen, Feiping Nie, Rongrong Ji, Xiaofang Zhou |
| 2011 | CVPR | Heterogeneous image feature integration via multi-modal spectral clustering. | Xiao Cai, Feiping Nie, Heng Huang, Farhad Kamangar |
| 2011 | CVPR | Tag localization with spatial correlations and joint group sparsity. | Yang Yang, Yi Yang, Zi Huang, Heng Tao Shen, Feiping Nie |
| 2011 | ICCV | Unsupervised and semi-supervised learning via ℓ1-norm graph. | Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding |
| 2011 | ICCV | Dyadic transfer learning for cross-domain image classification. | Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2011 | ICCV | Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. | Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen |
| 2011 | ICDE | Consensus spectral clustering in near-linear time. | Dijun Luo, Chris H. Q. Ding, Heng Huang, Feiping Nie |
| 2011 | ICDM | Multi-Class L2, 1-Norm Support Vector Machine. | Xiao Cai, Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2011 | ICDM | Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation. | Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding |
| 2011 | ICML | Cauchy Graph Embedding. | Dijun Luo, Chris H. Q. Ding, Feiping Nie, Heng Huang |
| 2011 | IJCAI | Feature Selection via Joint Embedding Learning and Sparse Regression. | Chenping Hou, Feiping Nie, Dongyun Yi, Yi Wu |
| 2011 | IJCAI | Robust Principal Component Analysis with Non-Greedy l | Feiping Nie, Heng Huang, Chris H. Q. Ding, Dijun Luo, Hua Wang |
| 2011 | IJCAI | Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering. | Hua Wang, Feiping Nie, Heng Huang, Fillia Makedon |
| 2011 | MDAI | Semi-supervised Dimensionality Reduction via Harmonic Functions. | Chenping Hou, Feiping Nie, Yi Wu |
| 2011 | MICCAI | Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. | Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen |
| 2011 | SIGIR | Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization. | Hua Wang, Heng Huang, Feiping Nie, Chris H. Q. Ding |
| 2010 | AAAI | Local and Global Regressive Mapping for Manifold Learning with Out-of-Sample Extrapolation. | Yi Yang, Feiping Nie, Shiming Xiang, Yueting Zhuang, Wenhua Wang |
| 2010 | ICIP | Regularized Trace Ratio Discriminant Analysis with Patch Distribution Feature for human gait recognition. | Yi Huang, Dong Xu, Feiping Nie |
| 2009 | CIKM | Efficient multi-class unlabeled constrained semi-supervised SVM. | Mingjie Qian, Feiping Nie, Changshui Zhang |
| 2009 | ICDM | Probabilistic Labeled Semi-supervised SVM. | Mingjie Qian, Feiping Nie, Changshui Zhang |
| 2009 | IJCAI | Spectral Embedded Clustering. | Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang |
| 2008 | AAAI | Trace Ratio Criterion for Feature Selection. | Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang, Shuicheng Yan |
| 2007 | CVPR | Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition. | Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang |
| 2007 | ICASSP | Extracting the Optimal Dimensionality for Discriminant Analysis. | Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang |
| 2007 | IJCAI | Neighborhood MinMax Projections. | Feiping Nie, Shiming Xiang, Changshui Zhang |
| 2007 | MMM | Interactive Visual Object Extraction Based on Belief Propagation. | Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang |
| 2007 | PAKDD | Embedding New Data Points for Manifold Learning Via Coordinate Propagation. | Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang, Chunxia Zhang |
| 2006 | ACCV | Texture Image Segmentation: An Interactive Framework Based on Adaptive Features and Transductive Learning. | Shiming Xiang, Feiping Nie, Changshui Zhang |
| 2006 | ACCV | Exemplar-Based Human Contour Tracking. | Shiming Xiang, Feiping Nie, Changshui Zhang |
| 2006 | ACCV | Contour Matching Based on Belief Propagation. | Shiming Xiang, Feiping Nie, Changshui Zhang |