Publications
2024
William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu, Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery, AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
Fanfan Ji, Xiao-Tong Yuan, Qingshan Liu, Soft Weight Pruning for Cross-Domain Few-Shot Learning with Unlabeled Target Data, IEEE Transactions on Multimedia, accepted, 2024.
2023
Xiao-Tong Yuan, Ping Li, $L_2$-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting, Neural Information Processing Systems (NeurIPS), 2023. [PDF]
Xiao-Tong Yuan, Ping Li, Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms, International Conference on Learning Representations (ICLR), 2023. [PDF]
Xiao-Tong Yuan, Ping Li, Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation, Journal of Machine Learning Research (JMLR), 24(270): 1-52, 2023. [PDF]
Fanfan Ji, Yunpeng Chen, Luoqi Liu, Xiao-Tong Yuan, Cross-Domain Few-Shot Classification via Dense-Sparse-Dense Regularization, IEEE Transactions on Circuits and Systems for Video Technology (IEEE-TCSVT), 2023.
2022
Xiao-Tong Yuan, Ping Li, On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond, Neural Information Processing Systems (NeurIPS), 2022. [arxiv][PDF]
William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu. Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity, Neural Information Processing Systems (NeurIPS), 2022. [arxiv][PDF]
Xiao-Tong Yuan, Ping Li, Boosting the Confidence of Generalization for L2-Stable Randomized Learning Algorithms, preprint, 2022. [arxiv]
Xiao-Tong Yuan, Ping Li, Stability and Risk Bounds of Iterative Hard Thresholding, IEEE Transactions on Information Theory (IEEE-TIT), 68(10): 6663- 6681, 2022. [arxiv] [PDF]
Pan Zhou, Xiao-Tong Yuan, Zhouchen Lin, and Steven Hoi, A Hybrid Stochastic-Deterministic Minibatch Proximal Gradient Method for Efficient Optimization and Generalization, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI), 44(10): 5933-5946, 2022. [PDF]
Fanfan Ji, Hui Shuai, Xiao-Tong Yuan, A globally convergent approximate Newton method for non-convex sparse learning, Pattern Recognition, 126, 2022. [PDF]
Mei Xue, Renlong Hang, Xiao-Tong Yuan, Pengfei Xiao, Qingshan Liu, Global Tropical Cyclone Precipitation Estimation via a Multitask Convolutional Neural Network Based on HURSAT-B1 Data. IEEE Transactions on Geoscience and Remote Sensing (IEEE-TGRS), 60: 1-12, 2022. [PDF]
2021
Pan Zhou, Caiming Xiong, Xiao-Tong Yuan, Steven Hoi, A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning, Neural Information Processing Systems (NeurIPS), 2021. (Spotlight) [arxiv] [PDF]
Pan Zhou, Hanshu Yan, Xiao-Tong Yuan, Jiashi Feng, Shuicheng Yan, Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond, Neural Information Processing Systems (NeurIPS), 2021. [PDF]
Pan Zhou, Yingtian Zou, Xiao-Tong Yuan, Jiashi Feng, Caiming Xiong, and Steven Hoi, Task Similarity Aware Meta Learning: Theory-inspired Improvement on MAML, International Conference on Uncertainty in Artificial Intelligence (UAI), 2021. [PDF]
Kaihua Zhang, Mingliang Dong, Bo Liu, Xiao-Tong Yuan, Qingshan Liu, DeepACG: Co-Saliency Detection via Semantic-aware Contrast Gromov-Wasserstein Distance, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [PDF]
Xiao-Tong Yuan, Ping Li, Stability and Risk Bounds of Iterative Hard Thresholding, International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. [PDF]
Pan Zhou, Xiao-Tong Yuan, Shuicheng Yan, Jiashi Feng, Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI), 43(2): 459-472, 2021. (A short version appeared in AISTATS 2019.) [arxiv] [PDF]
Guangcan Liu, Qingshan Liu, Xiao-Tong Yuan, Meng Wang, Matrix Completion with Deterministic Sampling: Theories and Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI), 43(2): 459-472, 2021.
Mei Xue, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan, Xinyu Lu, CNN-based near-real-time precipitation estimation from Fengyun-2 satellite over Xinjiang, China, Atmospheric Research, 250: 105337, 2021. [PDF]
2020
Xiao-Tong Yuan, Ping Li, On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond, Journal of Machine Learning Research (JMLR), 21(206): 1−51, 2020. [PDF]
Hongduan Tian, Bo Liu, Xiaotong Yuan, Qingshan Liu, Meta-Learning with Network Pruning, European Conference on Computer Vision (ECCV), 2020. [PDF]
Xiao-Tong Yuan, Bo Liu, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas, Dual Iterative Hard Thresholding, Journal of Machine Learning Research (JMLR), 21(152): 1-50, 2020. [PDF]
Pan Zhou, Xiao-Tong Yuan, Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization, International Conference on Machine Learning (ICML), 2020. [PDF]
Xiao-Tong Yuan, Ping Li, Nearly Non-Expansive Bounds for Mahalanobis Hard Thresholding, Conference on Learning Theory (COLT), 2020. [PDF]
Xiao-Tong Yuan, Ping Li, Generalization Bounds for High-dimensional M-estimation under Sparsity Constraint, preprint, 2020. [arXiv]
Yubao Sun, Ying Yang, Qingshan Liu, Jiwei Chen, Xiao-Tong Yuan, Guodong Guo, Learning Non-Locally Regularized Compressed Sensing Network With Half-Quadratic Splitting. IEEE Transactions on Multimedia, 22(12): 3236-3248, 2020. [PDF]
2019
Feng Zhou, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan, Pyramid Fully Convolutional Network for Hyperspectral and Multispectral Image Fusion, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE-JSTARS), 12(5): 1549-1558, 2019.
Feng Zhou, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan, Hyperspectral image classification using spectral-spatial LSTMs, Neurocomputing, 328: 39-47, 2019.
Pan Zhou, Xiao-Tong Yuan, Huan Xu, Shuicheng Yan, Jiashi Feng, Efficient Meta Learning via Minibatch Proximal Update, Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2019. (Spotlight)
Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Junzhou Huang, Dimitris Metaxas, Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning, International Conference on Artificial Intelligence and Statistics (AISTATS), Okinawa, Japan, 2019.
Pan Zhou, Xiao-Tong Yuan, Shuicheng Yan, Jiashi Feng, Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds, International Conference on Artificial Intelligence and Statistics (AISTATS), Okinawa, Japan, 2019.
2018
Pan Zhou, Xiao-Tong Yuan, Jiashi Feng, Efficient Stochastic Gradient Hard Thresholding, Neural Information Processing Systems (NeurIPS), Montreal, Canada, 2018.
Pan Zhou, Xiao-Tong Yuan, Jiashi Feng, New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity, Neural Information Processing Systems (NeurIPS), Montreal, Canada, 2018.
Xiao-Tong Yuan, Ping Li, Tong Zhang, Gradient Hard Thresholding Pursuit, Journal of Machine Learning Research (JMLR), 18:1-43, 2018.
Qingshan Liu, Guangcan Liu, Lai Li, Xiao-Tong Yuan, Meng Wang, Wei Liu, Reversed Spectral Hashing, IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), 29(6): 2441-2449, 2018.
Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang, New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), London, UK, 2018.
Feng Zhou, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan, Integrating Convolutional Neural Network and Gated Recurrent Unit for Hyperspectral Image Spectral-Spatial Classification, Chinese Conference on Pattern Recognition and Computer Vision (PRCV), Guangzhou, China, 2018.
2017
Bo Liu, Xiao-Tong Yuan, Qingshan Liu, Dimitris Metaxas, Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning, the 10th NIPS Workshop on Optimization for Machine Learning (OPT), Long Beach, USA, 2017. [PDF]
Guangcan Liu, Qingshan Liu, Xiao-Tong Yuan, A New Theory for Nonconvex Matrix Completion, Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, USA, 2017.
Qingshan Liu, Feng Zhou, Renlong Hang, Xiaotong Yuan, Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification, Remote Sensing, 9(12): 1330, 2017. [arXiv]
Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan, Hyperspectral Image Classification Using Spectral-Spatial LSTMs. CCCV: 577-588, 2017.
Qingshan Liu, Guangcan Liu, Lai Li, Xiao-Tong Yuan, Meng Wang, Wei Liu, Reversed Spectral Hashing, IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), 2017.
Bo Liu, Xiao-Tong Yuan, Yang Yu, Qingshan Liu, Dimitris N. Metaxas, Parallel Sparse Subspace Clustering via Joint Sample and Parameter Blockwise Partition, ACM Transactions on Embedded Computing Systems, 16(3): 75:1-75:17, 2017.
Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas, Dual Iterative Hard Thresholding: From Nonconvex Sparse Minimization to Nonsmooth Concave Maximization, International Conference on Machine Learning (ICML), Sydney, Australia, 2017. [PDF][arXiv]
Xiao-Tong Yuan, Qingshan Liu, Newton-Type Greedy Selection Methods for L0-Constrained Minimization, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI), 39(12): 2437-2450, 2017.
Jun Li, Tong Zhang, Wei Luo, Jian Yang, Xiao-Tong Yuan, Jian Zhang, Sparseness Analysis in the Pretraining of Deep Neural Networks, IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), 28(6): 1425-1438, 2017. [PDF]
Renlong Hang, Qingshan Liu, Yubao Sun, Xiaotong Yuan, Hucheng Pei, Javier Plaza, Antonio Plaza. Robust Matrix Discriminative Analysis for Feature Extraction From Hyperspectral Images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE-JSTARS), 10(5): 2002-2011, 2017.
2016
Xiao-Tong Yuan, Zhenzhen Wang, Jiankang Deng, Qingshan Liu, Efficient χ2 Kernel Linearization via Random Feature Maps, IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS), 27(11): 2448-2453, 2016. [PDF]
Xiao-Tong Yuan, Ping Li, Tong Zhang, Exact Recovery of Hard Thresholding Pursuit, Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016. [PDF]
Xiao-Tong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu, Learning Additive Exponential Family Graphical Models via ℓ2,1-norm Regularized M-Estimation, Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016. [PDF]
Xiaojie Jin, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan, Training Skinny Deep Neural Networks with Iterative Hard Thresholding Methods, preprint, 2016.[arXiv]
Bo Liu, Xiao-Tong Yuan, Shaoting Zhang, Qingshan Liu, Dimitris N. Metaxas, Efficient k-Support-Norm Regularized Minimization via Fully Corrective Frank-Wolfe Method, International Joint Conference on Artificial Intelligence (IJCAI), New York City, USA, 2016. [PDF]
Bo Liu, Xiao-Tong Yuan, Yang Yu, Qingshan Liu, Dimitris N. Metaxas,Decentralized Robust Subspace Clustering, AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona USA, 2016. [PDF]
Yan-Ming Zhang, Xu-Yao Zhang, Xiao-Tong Yuan, Cheng-Lin Liu, Large-Scale Graph-based Semi-Supervised Learning via Tree Laplacian Solver, AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona USA, 2016. [PDF]
2015
Zhenzhen Wang, Xiao-Tong Yuan, Qingshan Liu, Shuicheng Yan, Additive Nearest Neighbor Feature Maps, IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015. [PDF]
Zhenzhen Wang, Xiao-Tong Yuan, Qingshan Liu, Sparse random projection for χ2 kernel linearization: Algorithm and applications to image classification, Neurocomputing, 151:327-332, 2015. [PDF]
2014
Jiashi Feng, Xiao-Tong Yuan, Zilei Wang, Huan Xu and Shuicheng Yan, Auto-grouped Sparse Representations for Visual Analysis, IEEE Transactions on Image Processing (IEEE-TIP), 23(12): 5390-5399, 2014. [PDF]
Ran He, Bao-Gang Hu, Xiaotong Yuan, Liang Wang, Robust Recognition via Information Theoretic Learning, Springer Briefs in Computer Science, Springer 2014, ISBN 978-3-319-07415-3. [PDF]
Xiao-Tong Yuan, Ping Li, Sparse Additive Subspace Clustering, European Conference on Computer Vision (ECCV), Zurich, Switzerland, 2014. [PDF]
Xiao-Tong Yuan, Ping Li, Tong Zhang, Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization, International Conference on Machine Learning (ICML), Beijing, China, 2014. [PDF] [arXiv]
Xiao-Tong Yuan, Qingshan Liu, Newton Greedy Pursuit: a Quadratic Approximation Method for Sparsity-Constrained Optimization, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, 2014. [PDF]
Xiao-Tong Yuan, Tong Zhang, Partial Gaussian Graphical Model Estimation, IEEE Transactions on Information Theory, 60(3):1673-1687, 2014. [PDF][arXiv]
Jun Li, Jian Yang, Xiaotong Yuan, Zhaohua Hu, Continuous attractors of higher-order recurrent neural networks with infinite neurons, Neurocomputing, 131:388-396, 2014. [PDF]
Bineng Zhong, Xiaotong Yuan, Rongrong Ji, Yan Yan, Zhen Cui, Xiaopeng Hong, Yan Chen, Tian Wang, Duansheng Chen, Jiaxin Yu, Structured partial least squares for simultaneous object tracking and segmentation, Neurocomputing, 133:317-327, 2014. [PDF]
2013
Xiao-Tong Yuan, Ping Li, Tong Zhang, Learning Pairwise Graphical Models with Nonlinear Sufficient Statistics, preprint, 2013. [arXiv]
Xiao-Tong Yuan, Tong Zhang, Xiu-Feng Wan, A Joint Matrix Completion and Filtering Model for Influenza Serological Data Integration, PLOS ONE, 8(7): 1-12, 2013. [PDF].
Xiao-Tong Yuan, Tong Zhang, Truncated Power Method for Sparse Eigenvalue Problems, Journal of Machine Learning Research (JMLR), 14: 899-925, 2013. [PDF][arXiv][CODE]
Xiao-Tong Yuan, Shuicheng Yan, Forward Basis Selection for Pursuing Sparse Representations Over a Dictionary, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI), 35(12): 3025-3036, 2013. [PDF]
Ran He, Xiao-Tong Yuan and Wei-Shi Zheng, A Fast Convex Conjugated Algorithm for Sparse Recovery, Neurocomputing, 115(4): 178-185, 2013. [PDF]
Bin Fan, Qingqun Kong, Xiao-Tong Yuan, Zhiheng Wang, Chunhong Pan, Learning Weighted Hamming Distance For Binary Descriptors, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2013. [PDF]
Congyan Lang, Songhe Feng, Bin Chen, Xiao-Tong Yuan, Supervised sparse patch coding towards misalignment-robust face recognition, Journal of Visual Communication and Image Representation, 24(2): 103-110, 2013. [PDF]
2012
Bao-Gang Hu, Ran He, Xiao-Tong Yuan, Information-theoretic Measures for Objective Evaluation of Classifications, ACTA AUTOMATICA SINICA, 38(7): 1169-1182, 2012. [PDF]
Xiao-Tong Yuan, Shuicheng Yan, Non-degenerate Piecewise Linear Systems: A Finite Newton Algorithm and Applications in Machine Learning, Neural Computation, Vol. 24, No. 4, Pages 1047-1084, 2012. [PDF]
Xiao-Tong Yuan, Xiaobai Liu and Shuicheng Yan, Visual Classification With Multitask Joint Sparse Representation, IEEE Transactions on Image Processing (IEEE-TIP), 21(10): 4349-4360, 2012. [PDF]
Xiao-Tong Yuan, Bao-Gang Hu and Ran He, Agglomerative Mean-Shift Clustering, IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE), 24(2): 209-219, 2012. [PDF] [CODE]
Jiashi Feng, Xiaotong Yuan, Zilei Wang, Huan Xu, Shuicheng Yan, Auto-grouped Sparse Representation for Visual Analysis, European Conference on Computer Vision (ECCV), 2012. [PDF]
Xiao-Tong Yuan, Shuicheng Yan, Forward Basis Selection for Sparse Approximation over Dictionary, International Conference on Artificial Intelligence and Statistics (AISTATS), 1377-1388, La Palma, Canary Islands, 2012. [PDF]
2011
Xiangyu Chen, Xiao-Tong Yuan, Shuicheng Yan, Jinhui Tang, Yong Rui and Tat-Seng Chua, Towards Multi-Semantic Image Annotation with Graph Regularized Exclusive Group Lasso, ACM Multimedia, Scottsdale, Arizona , USA, 2011. (Full paper) [PDF]
Xiangyu Chen, Xiao-Tong Yuan, Qiang Chen, Shuicheng Yan and Tat-Seng Chua, Multi-label Visual Classification with Label Exclusive Context, IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain, 2011. [PDF]
Xiaobai Liu, Xiao-Tong Yuan, Shuicheng Yan and Hai Jin, Multi-class Semi-supervised SVMs with Positiveness Exclusive Regularization, IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain, 2011. [PDF]
Shusen Wang, Xiao-Tong Yuan, Tiansheng Yao, Shuicheng Yan, Jialie Shen, Efficient Subspace Segmentation via Quadratic Programming, AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, USA, 2011. [PDF]
Xiao-Tong Yuan and Shuicheng Yan, A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems, International Conference on Artificial Intelligence and Statistics (AISTATS), Ft. Lauderdale, FL, USA, 2011. [PDF] [CODE]
Yadong Mu, Jian Dong, Xiao-Tong Yuan, Shuicheng Yan, Accelerated Low-Rank Visual Recovery by Random Projection, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs , USA, 2011, to appear. (Oral) [PDF]
Hui Yan, Xiao-Tong Yuan, Shuicheng Yan, Jingyu Yang, Correntropy based feature selection using binary projection, Pattern Recognition, 44(12): 2834-2842, 2011. [PDF]
2010
Yuzhao Ni, Ju Sun, Xiao-Tong Yuan, Shuicheng Yan, Loong-Fah Cheong, Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees, Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'10 in conjunction with ICDM2010) [PDF] [arXiv].
Mengdi Xu, Xiao-Tong Yuan, Jialie Shen, Shuicheng Yan, Cast2Face: Character Identification in Movie with Actor-Character Correspondence, ACM Multimedia, Firenze, Italy, 2010. (Short paper) [PDF]
Richang Hong, Xiao-Tong Yuan, Mengdi Xu, Meng Wang, Shuicheng Yan, Tat-Seng Chua, Movie2Comics: A Feast of Multimedia Artwork, ACM Multimedia, Firenze, Italy, 2010. (Short paper) [PDF]
Xiao-Tong Yuan and Shuicheng Yan, Visual Classification with Multi-Task Joint Sparse Representation, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, USA, 2010. (Oral) [PDF] [SLIDES] [CODE]
Bineng Zhong, Hongxun Yao, Sheng Chen, Rongrong Ji, Xiao-Tong Yuan, Shaohui Liu, Wen Gao, Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, 2010. [PDF]
Ran He, Bao-Gang Hu, Xiao-Tong Yuan and Wei-Shi Zheng, Principal component analysis based on non-parametric maximum entropy, Neurocomputing, Vol.73, Issue 10-12, pp.1840-1852, Jun. 2010. [PDF]
2009
Ran He, Bao-Gang Hu and Xiao-Tong Yuan, Robust Discriminant Analysis Based on Nonparametric Maximum Entropy, Asian Conference on Machine Learning (ACML), Nanjing, China, 2009. [PDF]
Xiao-Tong Yuan and Bao-Gang Hu, Robust Feature Extraction via Information Theoretic Learning, International Conference on Machine Learning (ICML), Montreal, Canada. 2009. [PDF] [SLIDES] [CODE]
Xiao-Tong Yuan and Stan Z. Li, Stochastic Gradient Kernel Density Mode-Seeking, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida, USA. 2009. [PDF]
Xiao-Tong Yuan, Bao-Gang Hu and Ran He, Agglomerative Mean-Shift Clustering via Query Set Compression, SIAM International Conference on Data Mining (SDM), Sparks, USA, April 30-May 2, 2009. (Oral) [PDF]
2008
Rong Liu, Stan Z.Li, Xiaotong Yuan and Ran He, Online Determination of Track Loss Using Template Inverse Matching, IEEE International Workshop on Visual Surveillance, Marseille, France, October, 2008. [PDF]
Min Xu, Stan Z. Li, Bin Li, Xiao-Tong Yuan and Shi-Ming Xiang, A Set Theoretical Method for Video Synopsis, ACM International Conference on Multimedia Information Retrieval , Vancouver, Canada, October 30-31, 2008. [PDF]
Ran He, Zhen Lei, Xiao-Tong Yuan and Stan Z. Li, Regularized Active Shape Model for Shape Alignment, IEEE International Conference on Automatic Face and Gesture Recognition (FG), Amsterdam, The Netherlands, Sep. 17-19, 2008. [PDF]
2007
Xiao-Tong Yuan and Stan Z. Li, Half Quadratic Analysis for Mean Shift: with Extension to A Sequential Data Mode-Seeking Method, IEEE International Conference on Computer Vision (ICCV), Rio de Janeiro, Brazil, Oct. 14-20, 2007. (Oral) [PDF] [SLIDES]
Xiao-Tong Yuan, Stan Z. Li and Ran He, Color Constancy via Convex Kernel Optimization, Asian Conference on Computer Vision (ACCV), Tokyo, Japan, Nov. 18-22, 2007. [PDF] [POSTER]
Lun Zhang, Stan Z.Li, Xiao-Tong Yuan and Shiming Xiang, Real-time Object Classification in Video Surveillance Based on Appearance Learning, IEEE International Workshop on Visual Surveillance (in conjunction with CVPR), Minneapolis, USA, 2007. [PDF]
Shengcai Liao, Zhen Lei, Stan Z. Li, Xiao-Tong Yuan and Ran He, Structured Ordinal Features for Appearance-Based Object Representation, IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG), in conjunction with ICCV, Rio de Janeiro, Brazil, Oct. 14-20, 2007. [PDF]
2006
Xiao-Tong Yuan and Stan Z. Li, A Random Field Model for Improved Feature Extraction and Tracking, IEEE International Conference on Video and Signal Based Surveillance , Sydney, Ausralia, Nov. 22-24,2006. [PDF]
Xiao-Tong Yuan and Stan Z. Li, Learning Feature Extraction and Classification for Tracking Multiple Objects: A Unified Framework, IEEE International Conference on Video and Signal Based Surveillance, Sydney, Ausralia, Nov. 22-24,2006. [PDF]