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ORCIDXiao-Tong Yuan
Xiaotong Yuan
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- affiliation: Nanjing University of Information Science and Technology, China
- affiliation (former): Department of Statistics and Biostatistics, Rutgers University
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2020 – today
- 2024
[j46]Huayong Zhang, Xiaotong Yuan, Hengchao Zou
, Lei Zhao, Zhongyu Wang, Fenglu Guo, Zhao Liu:
The Spatiotemporal Dynamics of Insect Predator-Prey System Incorporating Refuge Effect. Entropy 26(3): 196 (2024)- [j45]Zefeng Pan, Fanfan Ji, Yunlong Zhou, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan:
Deep Precipitation Nowcasting With Dual Regions Displacement Information and Global Spatiotemporal Representations Learning. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [j44]Yunlong Zhou, Renlong Hang, Fanfan Ji, Zefeng Pan, Qingshan Liu, Xiao-Tong Yuan:
Spatiotemporal Enhanced Adversarial Network for Precipitation Nowcasting. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 7608-7620 (2024) - [j43]Fanfan Ji, Yunpeng Chen, Luoqi Liu, Xiao-Tong Yuan:
Cross-Domain Few-Shot Classification via Dense-Sparse-Dense Regularization. IEEE Trans. Circuits Syst. Video Technol. 34(3): 1352-1363 (2024) - [j42]Zefeng Pan, Renlong Hang, Qingshan Liu, Xiao-Tong Yuan:
A Short-Long Term Sequence Learning Network for Precipitation Nowcasting. IEEE Trans. Geosci. Remote. Sens. 62: 1-14 (2024) - [j41]Fanfan Ji, Xiao-Tong Yuan, Qingshan Liu:
Soft Weight Pruning for Cross-Domain Few-Shot Learning With Unlabeled Target Data. IEEE Trans. Multim. 26: 6759-6769 (2024) - [c68]William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu:
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery. AAAI 2024: 11731-11739 - [i23]William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu:
Iterative Regularization with k-Support Norm: An Important Complement to Sparse Recovery. CoRR abs/2401.05394 (2024) - 2023
- [j40]Varun Mannam, Jacob Brandt, Cody J. Smith, Xiaotong Yuan, Scott S. Howard:
Improving fluorescence lifetime imaging microscopy phasor accuracy using convolutional neural networks. Frontiers Bioinform. 3 (2023) - [j39]Xiao-Tong Yuan, Ping Li:
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation. J. Mach. Learn. Res. 24: 270:1-270:52 (2023) - [c67]Minghui Miao, Shuo Fang, Weijie Wu, Xiaotong Yuan, Lin Bi:
Minimum Path Cost Multi-path Routing Algorithm with No Intersecting Links in Quantum Key Distribution Networks. ICISCAE 2023: 232-237 - [c66]Xiaotong Yuan, Ping Li:
Exponential Generalization Bounds with Near-Optimal Rates for $L_q$-Stable Algorithms. ICLR 2023 - [c65]Xiaotong Yuan, Ping Li:
L2-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting. NeurIPS 2023 - [i22]Xiao-Tong Yuan, Ping Li:
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation. CoRR abs/2301.03125 (2023) - 2022
- [j38]Pan Zhou, Xiao-Tong Yuan, Zhouchen Lin, Steven C. H. Hoi:
A Hybrid Stochastic-Deterministic Minibatch Proximal Gradient Method for Efficient Optimization and Generalization. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 5933-5946 (2022) - [j37]Fanfan Ji, Hui Shuai, Xiao-Tong Yuan:
A globally convergent approximate Newton method for non-convex sparse learning. Pattern Recognit. 126: 108560 (2022) - [j36]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 Trans. Geosci. Remote. Sens. 60: 1-12 (2022) - [j35]Xiao-Tong Yuan, Ping Li:
Stability and Risk Bounds of Iterative Hard Thresholding. IEEE Trans. Inf. Theory 68(10): 6663-6681 (2022) - [c64]William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu:
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. NeurIPS 2022 - [c63]Xiaotong Yuan, Ping Li:
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond. NeurIPS 2022 - [i21]Xiao-Tong Yuan, Ping Li:
Stability and Risk Bounds of Iterative Hard Thresholding. CoRR abs/2203.09413 (2022) - [i20]Xiao-Tong Yuan, Ping Li:
Boosting the Confidence of Generalization for L2-Stable Randomized Learning Algorithms. CoRR abs/2206.03834 (2022) - [i19]Xiao-Tong Yuan, Ping Li:
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond. CoRR abs/2206.05187 (2022) - [i18]William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu:
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. CoRR abs/2210.05279 (2022) - 2021
- [j34]Pan Zhou, Xiao-Tong Yuan, Shuicheng Yan, Jiashi Feng:
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 459-472 (2021) - [j33]Guangcan Liu, Qingshan Liu, Xiao-Tong Yuan, Meng Wang:
Matrix Completion with Deterministic Sampling: Theories and Methods. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 549-566 (2021) - [c62]Xiaotong Yuan, Ping Li:
Stability and Risk Bounds of Iterative Hard Thresholding. AISTATS 2021: 1702-1710 - [c61]Kaihua Zhang, Mingliang Dong, Bo Liu, Xiao-Tong Yuan, Qingshan Liu:
DeepACG: Co-Saliency Detection via Semantic-Aware Contrast Gromov-Wasserstein Distance. CVPR 2021: 13703-13712 - [c60]Pan Zhou, Caiming Xiong, Xiaotong Yuan, Steven Chu-Hong Hoi:
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning. NeurIPS 2021: 6183-6197 - [c59]Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan:
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond. NeurIPS 2021: 27290-27304 - [c58]Pan Zhou, Yingtian Zou, Xiao-Tong Yuan, Jiashi Feng, Caiming Xiong, Steven C. H. Hoi:
Task similarity aware meta learning: theory-inspired improvement on MAML. UAI 2021: 23-33 - [i17]Varun Mannam, Yide Zhang, Xiaotong Yuan, Scott S. Howard:
Deep learning-based super-resolution fluorescence microscopy on small datasets. CoRR abs/2103.04989 (2021) - [i16]Varun Mannam, Yide Zhang, Xiaotong Yuan, Takashi Hato, Pierre C. Dagher, Evan L. Nichols, Cody J. Smith, Kenneth W. Dunn, Scott S. Howard:
Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM). CoRR abs/2103.05448 (2021) - [i15]Pan Zhou, Caiming Xiong, Xiao-Tong Yuan, Steven C. H. Hoi:
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning. CoRR abs/2106.14749 (2021) - 2020
- [j32]Xiao-Tong Yuan, Bo Liu, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas:
Dual Iterative Hard Thresholding. J. Mach. Learn. Res. 21: 152:1-152:50 (2020) - [j31]Xiao-Tong Yuan, Ping Li:
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond. J. Mach. Learn. Res. 21: 206:1-206:51 (2020) - [j30]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 Trans. Multim. 22(12): 3236-3248 (2020) - [c57]Xiao-Tong Yuan, Ping Li:
Nearly Non-Expansive Bounds for Mahalanobis Hard Thresholding. COLT 2020: 3787-3813 - [c56]Hongduan Tian, Bo Liu, Xiao-Tong Yuan, Qingshan Liu:
Meta-learning with Network Pruning. ECCV (19) 2020: 675-700 - [c55]Pan Zhou, Xiao-Tong Yuan:
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization. ICML 2020: 11556-11565 - [c54]Jue Wang, Fanfan Ji, Xiao-Tong Yuan:
Pruning Deep Convolutional Neural Networks via Gradient Support Pursuit. PRCV (3) 2020: 419-432 - [i14]Hongduan Tian, Bo Liu, Xiao-Tong Yuan, Qingshan Liu:
Meta-Learning with Network Pruning. CoRR abs/2007.03219 (2020) - [i13]Varun Mannam, Yide Zhang, Xiaotong Yuan, Cara Ravasio, Scott S. Howard:
Machine learning for faster and smarter fluorescence lifetime imaging microscopy. CoRR abs/2008.02320 (2020) - [i12]Pan Zhou, Xiaotong Yuan:
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization. CoRR abs/2009.09835 (2020)
2010 – 2019
- 2019
- [j29]Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan:
Hyperspectral image classification using spectral-spatial LSTMs. Neurocomputing 328: 39-47 (2019) - [j28]Yahui Wang, Bo Liu, Xiaotong Yuan:
基于近似牛顿法的分布式卷积神经网络训练 (Distributed Convolutional Neural Networks Based on Approximate Newton-type Mothod). 计算机科学 46(7): 180-185 (2019) - [j27]Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan:
Pyramid Fully Convolutional Network for Hyperspectral and Multispectral Image Fusion. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(5): 1549-1558 (2019) - [c53]Pan Zhou, Xiao-Tong Yuan, Jiashi Feng:
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds. AISTATS 2019: 138-147 - [c52]Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Junzhou Huang, Dimitris N. Metaxas:
Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning. AISTATS 2019: 343-352 - [c51]Pan Zhou, Xiaotong Yuan, Huan Xu, Shuicheng Yan, Jiashi Feng:
Efficient Meta Learning via Minibatch Proximal Update. NeurIPS 2019: 1532-1542 - [c50]Fanfan Ji, Hui Shuai, Xiao-Tong Yuan:
Quadratic Approximation Greedy Pursuit for Cardinality-Constrained Sparse Learning. PRCV (1) 2019: 337-348 - [c49]Xin Yang, Haiwei Lu, Hui Shuai, Xiao-Tong Yuan:
Pruning Convolutional Neural Networks via Stochastic Gradient Hard Thresholding. PRCV (1) 2019: 373-385 - [i11]Xiao-Tong Yuan, Ping Li:
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond. CoRR abs/1908.02246 (2019) - 2018
- [j26]Qingshan Liu, Guangcan Liu, Lai Li, Xiao-Tong Yuan, Meng Wang, Wei Liu:
Reversed Spectral Hashing. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2441-2449 (2018) - [c48]Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang:
New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine. KDD 2018: 1475-1484 - [c47]Pan Zhou, Xiaotong Yuan, Jiashi Feng:
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity. NeurIPS 2018: 1242-1251 - [c46]Pan Zhou, Xiaotong Yuan, Jiashi Feng:
Efficient Stochastic Gradient Hard Thresholding. NeurIPS 2018: 1988-1997 - [c45]Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan:
Integrating Convolutional Neural Network and Gated Recurrent Unit for Hyperspectral Image Spectral-Spatial Classification. PRCV (4) 2018: 409-420 - [i10]Guangcan Liu, Qingshan Liu, Xiao-Tong Yuan, Meng Wang:
Matrix Completion with Nonuniform Sampling: Theories and Methods. CoRR abs/1805.02313 (2018) - 2017
- [j25]Xiao-Tong Yuan, Ping Li, Tong Zhang:
Gradient Hard Thresholding Pursuit. J. Mach. Learn. Res. 18: 166:1-166:43 (2017) - [j24]Xiao-Tong Yuan, Qingshan Liu:
Newton-Type Greedy Selection Methods for ℓ0-Constrained Minimization. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2437-2450 (2017) - [j23]Qingshan Liu, Feng Zhou, Renlong Hang, Xiaotong Yuan:
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification. Remote. Sens. 9(12): 1330 (2017) - [j22]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 J. Sel. Top. Appl. Earth Obs. Remote. Sens. 10(5): 2002-2011 (2017) - [j21]Bo Liu, Xiao-Tong Yuan, Yang Yu, Qingshan Liu, Dimitris N. Metaxas:
Parallel Sparse Subspace Clustering via Joint Sample and Parameter Blockwise Partition. ACM Trans. Embed. Comput. Syst. 16(3): 75:1-75:17 (2017) - [j20]Jun Li, Tong Zhang, Wei Luo, Jian Yang, Xiao-Tong Yuan, Jian Zhang:
Sparseness Analysis in the Pretraining of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 28(6): 1425-1438 (2017) - [c44]Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan:
Hyperspectral Image Classification Using Spectral-Spatial LSTMs. CCCV (1) 2017: 577-588 - [c43]Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas:
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization. ICML 2017: 2179-2187 - [c42]Guangcan Liu, Qingshan Liu, Xiaotong Yuan:
A New Theory for Matrix Completion. NIPS 2017: 785-794 - [i9]Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas:
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization. CoRR abs/1703.00119 (2017) - [i8]Qingshan Liu, Feng Zhou, Renlong Hang, Xiaotong Yuan:
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification. CoRR abs/1703.07910 (2017) - 2016
- [j19]Xiao-Tong Yuan, Zhenzhen Wang, Jiankang Deng, Qingshan Liu:
Efficient χ2 Kernel Linearization via Random Feature Maps. IEEE Trans. Neural Networks Learn. Syst. 27(11): 2448-2453 (2016) - [c41]Yan-Ming Zhang, Xu-Yao Zhang, Xiao-Tong Yuan, Cheng-Lin Liu:
Large-Scale Graph-Based Semi-Supervised Learning via Tree Laplacian Solver. AAAI 2016: 2344-2350 - [c40]Bo Liu, Xiao-Tong Yuan, Yang Yu, Qingshan Liu, Dimitris N. Metaxas:
Decentralized Robust Subspace Clustering. AAAI 2016: 3539-3545 - [c39]Bo Liu, Xiao-Tong Yuan, Shaoting Zhang, Qingshan Liu, Dimitris N. Metaxas:
Efficient k-Support-Norm Regularized Minimization via Fully Corrective Frank-Wolfe Method. IJCAI 2016: 1760-1766 - [c38]Xiao-Tong Yuan, Ping Li, Tong Zhang:
Exact Recovery of Hard Thresholding Pursuit. NIPS 2016: 3558-3566 - [c37]Xiao-Tong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu:
Learning Additive Exponential Family Graphical Models via \ell_{2, 1}-norm Regularized M-Estimation. NIPS 2016: 4367-4375 - [c36]Kedong Yin, Xiaotong Yuan, Xuemei Li, Shengmin Fang:
Grey relational analysis based on velocity and acceleration and its application. SMC 2016: 4283-4286 - [i7]Xiaojie Jin, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan:
Training Skinny Deep Neural Networks with Iterative Hard Thresholding Methods. CoRR abs/1607.05423 (2016) - 2015
- [j18]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) - [c35]Zhenzhen Wang, Xiao-Tong Yuan, Qingshan Liu, Shuicheng Yan:
Additive Nearest Neighbor Feature Maps. ICCV 2015: 2866-2874 - 2014
- [b1]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, pp. 1-102 - [j17]Bineng Zhong, Yan Chen, Yingju Shen, Yewang Chen, Zhen Cui, Rongrong Ji, Xiaotong Yuan, Duansheng Chen, Weibin Chen:
Robust tracking via patch-based appearance model and local background estimation. Neurocomputing 123: 344-353 (2014) - [j16]Jun Li, Jian Yang, Xiaotong Yuan, Zhaohua Hu:
Continuous attractors of higher-order recurrent neural networks with infinite neurons. Neurocomputing 131: 388-396 (2014) - [j15]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) - [j14]Jiashi Feng, Xiao-Tong Yuan, Zilei Wang, Huan Xu, Shuicheng Yan:
Autogrouped Sparse Representation for Visual Analysis. IEEE Trans. Image Process. 23(12): 5390-5399 (2014) - [j13]Xiao-Tong Yuan, Tong Zhang:
Partial Gaussian Graphical Model Estimation. IEEE Trans. Inf. Theory 60(3): 1673-1687 (2014) - [c34]Xiao-Tong Yuan, Qingshan Liu:
Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization. CVPR 2014: 4122-4129 - [c33]Xiao-Tong Yuan, Ping Li:
Sparse Additive Subspace Clustering. ECCV (3) 2014: 644-659 - [c32]Xiaotong Yuan, Ping Li, Tong Zhang:
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization. ICML 2014: 127-135 - 2013
- [j12]Ran He, Xiaotong Yuan, Wei-Shi Zheng:
A fast convex conjugated algorithm for sparse recovery. Neurocomputing 115: 178-185 (2013) - [j11]Xiao-Tong Yuan, Tong Zhang:
Truncated power method for sparse eigenvalue problems. J. Mach. Learn. Res. 14(1): 899-925 (2013) - [j10]Congyan Lang, Songhe Feng, Bin Chen, Xiaotong Yuan:
Supervised sparse patch coding towards misalignment-robust face recognition. J. Vis. Commun. Image Represent. 24(2): 103-110 (2013) - [j9]Xiao-Tong Yuan, Shuicheng Yan:
Forward Basis Selection for Pursuing Sparse Representations over a Dictionary. IEEE Trans. Pattern Anal. Mach. Intell. 35(12): 3025-3036 (2013) - [c31]Bin Fan, Qingqun Kong, Xiaotong Yuan, Zhiheng Wang, Chunhong Pan:
Learning weighted Hamming distance for binary descriptors. ICASSP 2013: 2395-2399 - [i6]Xiao-Tong Yuan, Ping Li, Tong Zhang:
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization. CoRR abs/1311.5750 (2013) - [i5]Jun Li, Wei Luo, Jian Yang, Xiaotong Yuan:
Why does the unsupervised pretraining encourage moderate-sparseness? CoRR abs/1312.5813 (2013) - 2012
- [j8]Xiao-Tong Yuan, Shuicheng Yan:
Nondegenerate Piecewise Linear Systems: A Finite Newton Algorithm and Applications in Machine Learning. Neural Comput. 24(4): 1047-1084 (2012) - [j7]Xiao-Tong Yuan, Xiaobai Liu, Shuicheng Yan:
Visual Classification With Multitask Joint Sparse Representation. IEEE Trans. Image Process. 21(10): 4349-4360 (2012) - [j6]Xiao-Tong Yuan, Bao-Gang Hu, Ran He:
Agglomerative Mean-Shift Clustering. IEEE Trans. Knowl. Data Eng. 24(2): 209-219 (2012) - [j5]Meng Wang, Richang Hong, Xiao-Tong Yuan, Shuicheng Yan, Tat-Seng Chua:
Movie2Comics: Towards a Lively Video Content Presentation. IEEE Trans. Multim. 14(3-2): 858-870 (2012) - [c30]Jiashi Feng, Xiaotong Yuan, Zilei Wang, Huan Xu, Shuicheng Yan:
Auto-Grouped Sparse Representation for Visual Analysis. ECCV (1) 2012: 640-653 - [c29]Xiaotong Yuan, Shuicheng Yan:
Forward Basis Selection for Sparse Approximation over Dictionary. AISTATS 2012: 1377-1388 - [i4]Xiao-Tong Yuan, Tong Zhang:
Partial Gaussian Graphical Model Estimation. CoRR abs/1209.6419 (2012) - 2011
- [j4]Hui Yan, Xiaotong Yuan, Shuicheng Yan, Jingyu Yang:
Correntropy based feature selection using binary projection. Pattern Recognit. 44(12): 2834-2842 (2011) - [j3]Richang Hong, Meng Wang, Xiao-Tong Yuan, Mengdi Xu, Jianguo Jiang, Shuicheng Yan, Tat-Seng Chua:
Video accessibility enhancement for hearing-impaired users. ACM Trans. Multim. Comput. Commun. Appl. 7(Supplement): 24 (2011) - [c28]Shusen Wang, Xiaotong Yuan, Tiansheng Yao, Shuicheng Yan, Jialie Shen:
Efficient Subspace Segmentation via Quadratic Programming. AAAI 2011: 519-524 - [c27]Yadong Mu, Jian Dong, Xiaotong Yuan, Shuicheng Yan:
Accelerated low-rank visual recovery by random projection. CVPR 2011: 2609-2616 - [c26]Xiangyu Chen, Xiao-Tong Yuan, Qiang Chen, Shuicheng Yan, Tat-Seng Chua:
Multi-label visual classification with label exclusive context. ICCV 2011: 834-841 - [c25]Xiaobai Liu, Xiaotong Yuan, Shuicheng Yan, Hai Jin:
Multi-class semi-supervised SVMs with Positiveness Exclusive Regularization. ICCV 2011: 1435-1442 - [c24]Congyan Lang, Bin Cheng, Songhe Feng, Xiao-Tong Yuan:
Supervised Sparse Patch Coding towards Misalignment-Robust Face Recognition. ICIG 2011: 599-604 - [c23]Xiangyu Chen, Xiaotong Yuan, Shuicheng Yan, Jinhui Tang, Yong Rui, Tat-Seng Chua:
Towards multi-semantic image annotation with graph regularized exclusive group lasso. ACM Multimedia 2011: 263-272 - [c22]Xiaotong Yuan, Shuicheng Yan:
A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems. AISTATS 2011: 841-854 - [i3]Bao-Gang Hu, Ran He, Xiaotong Yuan:
Information-Theoretic Measures for Objective Evaluation of Classifications. CoRR abs/1107.1837 (2011) - [i2]Xiao-Tong Yuan, Tong Zhang:
Truncated Power Method for Sparse Eigenvalue Problems. CoRR abs/1112.2679 (2011) - 2010
- [j2]Bineng Zhong, Hongxun Yao, Shaohui Liu, Xiaotong Yuan:
Local Histogram of Figure/Ground Segmentations for Dynamic Background Subtraction. EURASIP J. Adv. Signal Process. 2010 (2010) - [j1]Ran He, Bao-Gang Hu, Xiaotong Yuan, Wei-Shi Zheng:
Principal component analysis based on non-parametric maximum entropy. Neurocomputing 73(10-12): 1840-1852 (2010) - [c21]Bineng Zhong, Hongxun Yao, Sheng Chen, Rongrong Ji, Xiaotong Yuan, Shaohui Liu, Wen Gao:
Visual tracking via weakly supervised learning from multiple imperfect oracles. CVPR 2010: 1323-1330 - [c20]Xiaotong Yuan, Shuicheng Yan:
Visual classification with multi-task joint sparse representation. CVPR 2010: 3493-3500 - [c19]Yuzhao Ni, Ju Sun, Xiaotong Yuan, Shuicheng Yan, Loong Fah Cheong:
Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees. ICDM Workshops 2010: 1179-1188 - [c18]Richang Hong, Xiaotong Yuan, Mengdi Xu, Meng Wang, Shuicheng Yan, Tat-Seng Chua:
Movie2Comics: a feast of multimedia artwork. ACM Multimedia 2010: 611-614 - [c17]Mengdi Xu, Xiaotong Yuan, Jialie Shen, Shuicheng Yan:
Cast2Face: character identification in movie with actor-character correspondence. ACM Multimedia 2010: 831-834 - [c16]Richang Hong, Meng Wang, Guangda Li, Xiaotong Yuan, Shuicheng Yan, Tat-Seng Chua:
iComics: automatic conversion of movie into comics. ACM Multimedia 2010: 1599-1602 - [i1]Yuzhao Ni, Ju Sun, Xiaotong Yuan, Shuicheng Yan, Loong Fah Cheong:
Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees. CoRR abs/1009.3802 (2010)
2000 – 2009
- 2009
- [c15]Ran He, Bao-Gang Hu, Xiaotong Yuan:
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy. ACML 2009: 120-134 - [c14]Xiaotong Yuan, Stan Z. Li:
Stochastic gradient kernel density mode-seeking. CVPR 2009: 1926-1931 - [c13]Xiaotong Yuan, Bao-Gang Hu:
Robust feature extraction via information theoretic learning. ICML 2009: 1193-1200 - [c12]Xiaotong Yuan, Bao-Gang Hu, Ran He:
Agglomerative Mean-Shift Clustering via Query Set Compression. SDM 2009: 223-234 - 2008
- [c11]Ran He, Zhen Lei, Xiaotong Yuan, Stan Z. Li:
Regularized active shape model for shape alignment. FG 2008: 1-6 - [c10]Min Xu, Stan Z. Li, Bin Li, Xiaotong Yuan, Shiming Xiang:
A set theoretical method for video synopsis. Multimedia Information Retrieval 2008: 366-370 - 2007
- [c9]Xiaotong Yuan, Stan Z. Li, Ran He:
Color Constancy Via Convex Kernel Optimization. ACCV (1) 2007: 728-737 - [c8]Shengcai Liao, Zhen Lei, Stan Z. Li, Xiaotong Yuan, Ran He:
Structured Ordinal Features for Appearance-Based Object Representation. AMFG 2007: 183-192 - [c7]Lun Zhang, Stan Z. Li, Xiaotong Yuan, Shiming Xiang:
Real-time Object Classification in Video Surveillance Based on Appearance Learning. CVPR 2007 - [c6]Xiaotong Yuan, Stan Z. Li:
Half Quadratic Analysis for Mean Shift: with Extension to A Sequential Data Mode-Seeking Method. ICCV 2007: 1-8 - 2006
- [c5]Xiaotong Yuan, Stan Z. Li:
Learning Feature Extraction and Classification for Tracking Multiple Objects: A Unified Framework. AVSS 2006: 22 - [c4]Xiaotong Yuan, Stan Z. Li:
A Random Field Model for Improved Feature Extraction and Tracking. AVSS 2006: 37 - 2005
- [c3]Feng Chen, Xiaotong Yuan, ShuTang Yang:
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking. ICIP (2) 2005: 406-409 - [c2]Xiaotong Yuan, HongWen Zhu, ShuTang Yang:
A Robust Framework For Eigenspace Image Reconstruction. WACV/MOTION 2005: 54-59 - [c1]Xiaotong Yuan, ShuTang Yang, HongWen Zhu:
Region Tracking via HMMF in Joint Feature-Spatial Space. WACV/MOTION 2005: 72-77
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-15 19:29 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
