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ORCIDHua Wang 0007
Person information
- affiliation: Colorado School of Mines, Department of Electrical Engineering and Computer Science, Golden, CO, USA
Other persons with the same name
- Hua Wang — disambiguation page
- Hua Wang 0001
![[0000-0002-3660-4290]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-3660-4290")
— Beijing Institute of Technology, School of Information and Electronics, China (and 2 more) - Hua Wang 0002 — Victoria University, Centre for Applied Informatics, Melbourne, Australia (and 1 more)
- Hua Wang 0003 — Georgia Southern University, Mathematical Sciences, Statesboro, GA, USA
- Hua Wang 0004 — Hunan University, College of Mathematics and Econometrics, Changsha, China (and 2 more)
- Hua Wang 0005 — State University of New York, University at Buffalo, NY, USA (and 1 more)
- Hua Wang 0006 — Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA, USA (and 3 more)
- Hua Wang 0008 — Huazhong University of Science and Technology, Wuhan, Hubei, China (and 1 more)
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2020 – today
- 2024
[j24]Lodewijk Brand, Hoon Seo, Lauren Zoe Baker, Carla Ellefsen, Jackson Sargent, Hua Wang:
A linear primal-dual multi-instance SVM for big data classifications. Knowl. Inf. Syst. 66(1): 307-338 (2024)- [j23]Xiangyu Li, Hua Wang:
On Mean-Optimal Robust Linear Discriminant Analysis. ACM Trans. Knowl. Discov. Data 18(8): 191:1-191:27 (2024) - 2023
- [c75]Xiangyu Li, Umberto Gherardi, Armand Ovanessians, Hua Wang:
Beyond the Simplex: Hadamard-Infused Deep Sparse Representations for Enhanced Similarity Measures. ICKG 2023: 168-175 - [c74]Xiangyu Li, Armand Ovanessians, Hua Wang:
Discovering Protein Interactions and Repurposing Drugs in SARS-CoV-2 (COVID-19) via Learning on Robust Multipartite Graphs. ICDM 2023: 289-298 - [c73]Xiangyu Li, Armand Ovanessians, Hua Wang:
Enriched Representation Learning for Longitudinal Chest X-ray Analysis: A Novel Approach for Improved Disease Detection and Localization. ICDM 2023: 1127-1132 - [c72]Hoon Seo, Hua Wang:
Fast Multi-Modal Multi-Instance Support Vector Machine for Fine-grained Chest X-ray Recognition. ICDM 2023: 1295-1300 - 2022
- [j22]Brian Reily, Peng Gao, Fei Han, Hua Wang, Hao Zhang:
Real-time recognition of team behaviors by multisensory graph-embedded robot learning. Int. J. Robotics Res. 41(8): 798-811 (2022) - [c71]Hoon Seo, Lodewijk Brand, Lucia Saldana Barco, Hua Wang:
Scalable Multi-Instance Multi-Shape Support Vector Machine for Whole Slide Breast Histopathology. ICKG 2022: 225-232 - [c70]Xiangyu Li, Hua Wang:
On Mean-Optimal Robust Linear Discriminant Analysis. ICDM 2022: 1047-1052 - [c69]Xiangyu Li, Hua Wang:
Adaptive Principal Component Analysis. SDM 2022: 486-494 - 2021
- [j21]Lyujian Lu, Hua Wang, Brian Reily, Hao Zhang:
Robust Real-Time Group Activity Recognition of Robot Teams. IEEE Robotics Autom. Lett. 6(2): 2052-2059 (2021) - [j20]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Li Shen, Heng Huang:
Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions. IEEE Trans. Biomed. Eng. 68(11): 3336-3346 (2021) - [j19]Kai Liu, Xiangyu Li, Zhihui Zhu, Lodewijk Brand, Hua Wang:
Factor-Bounded Nonnegative Matrix Factorization. ACM Trans. Knowl. Discov. Data 15(6): 111:1-111:18 (2021) - [j18]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Feiping Nie:
Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers. IEEE Trans. Medical Imaging 40(3): 891-904 (2021) - [c68]Hoon Seo, Lodewijk Brand, Hua Wang, Feiping Nie:
Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations. AAAI 2021: 522-530 - [c67]Lodewijk Brand, Lauren Zoe Baker, Hua Wang:
A multi-instance support vector machine with incomplete data for clinical outcome prediction of COVID-19. BCB 2021: 44:1-44:6 - [c66]Hoon Seo, Hua Wang:
Learning Deeply Enriched Representations of Longitudinal Imaging-Genetic Data to Predict Alzheimer's Disease Progression. BIBM 2021: 732-735 - [c65]Lodewijk Brand, Lauren Zoe Baker, Carla Ellefsen, Jackson Sargent, Hua Wang:
A Linear Primal-Dual Multi-Instance SVM for Big Data Classifications. ICDM 2021: 21-30 - 2020
- [j17]Lodewijk Brand, Xue Yang, Kai Liu, Saad Elbeleidy, Hua Wang, Hao Zhang, Feiping Nie:
Learning Robust Multilabel Sample Specific Distances for Identifying HIV-1 Drug Resistance. J. Comput. Biol. 27(4): 655-672 (2020) - [j16]Lodewijk Brand, Kai Nichols, Hua Wang, Li Shen, Heng Huang:
Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction. IEEE Trans. Medical Imaging 39(6): 1845-1855 (2020) - [c64]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang:
Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments. AAAI 2020: 817-824 - [c63]Lodewijk Brand, Braedon O'Callaghan, Anthony Sun, Hua Wang:
Task Balanced Multimodal Feature Selection to Predict the Progression of Alzheimer's Disease. BIBE 2020: 196-203 - [c62]Hoon Seo, Lodewijk Brand, Hua Wang:
Learning Semi-Supervised Representation Enrichment Using Longitudinal Imaging-Genetic Data. BIBM 2020: 1115-1118 - [c61]Lyujian Lu, Hua Wang, Saad Elbeleidy, Feiping Nie:
Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers. CVPR 2020: 4826-4835 - [c60]Lodewijk Brand, Kai Nichols, Hua Wang, Heng Huang, Li Shen:
Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification andRegression Model. PSB 2020: 7-18
2010 – 2019
- 2019
- [c59]Kai Liu, Hua Wang, Fei Han, Hao Zhang:
Visual Place Recognition via Robust ℓ2-Norm Distance Based Holism and Landmark Integration. AAAI 2019: 8034-8041 - [c58]Kai Liu, Lodewijk Brand, Hua Wang, Feiping Nie:
Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances. IJCAI 2019: 3008-3014 - [c57]Haoxuan Yang, Kai Liu, Hua Wang, Feiping Nie:
Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method. IJCAI 2019: 4040-4046 - [c56]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Heng Huang, Li Shen:
Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments over Progressions. MICCAI (4) 2019: 140-148 - [c55]Lodewijk Brand, Xue Yang, Kai Liu, Saad El Beleidy, Hua Wang, Hao Zhang:
Learning Robust Multi-label Sample Specific Distances for Identifying HIV-1 Drug Resistance. RECOMB 2019: 51-67 - [c54]Kai Liu, Qiuwei Li, Hua Wang, Gongguo Tang:
Spherical Principal Component Analysis. SDM 2019: 387-395 - [i3]Kai Liu, Qiuwei Li, Hua Wang, Gongguo Tang:
Spherical Principal Component Analysis. CoRR abs/1903.06877 (2019) - [i2]Feiping Nie, Hua Wang, Zheng Wang, Heng Huang:
Robust Linear Discriminant Analysis Using Ratio Minimization of L1, 2-Norms. CoRR abs/1907.00211 (2019) - 2018
- [j15]Fei Han, Hua Wang, Guoquan Huang, Hao Zhang:
Sequence-based sparse optimization methods for long-term loop closure detection in visual SLAM. Auton. Robots 42(7): 1323-1335 (2018) - [j14]Fei Han, Saad El Beleidy, Hua Wang, Cang Ye, Hao Zhang:
Learning of Holism-Landmark Graph Embedding for Place Recognition in Long-Term Autonomy. IEEE Robotics Autom. Lett. 3(4): 3669-3676 (2018) - [c53]Fei Han, Hua Wang, Hao Zhang:
Learning Integrated Holism-Landmark Representations for Long-Term Loop Closure Detection. AAAI 2018: 6501-6508 - [c52]Kai Liu, Hua Wang, Feiping Nie, Hao Zhang:
Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances. CVPR 2018: 7727-7735 - [c51]Kai Liu, Hua Wang:
High-Order Co-Clustering via Strictly Orthogonal and Symmetric L1-Norm Nonnegative Matrix Tri-Factorization. IJCAI 2018: 2454-2460 - [c50]Lyujian Lu, Hua Wang, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning. ISBI 2018: 545-548 - [c49]Kai Liu, Hua Wang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis. ISBI 2018: 1402-1405 - [c48]Lodewijk Brand, Hua Wang, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. MICCAI (1) 2018: 555-562 - 2017
- [j13]Hua Wang, Lin Yan, Heng Huang, Chris H. Q. Ding:
From Protein Sequence to Protein Function via Multi-Label Linear Discriminant Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 503-513 (2017) - [c47]Yun Liu, Yiming Guo, Hua Wang, Feiping Nie, Heng Huang:
Semi-Supervised Classifications via Elastic and Robust Embedding. AAAI 2017: 2294-2300 - 2016
- [c46]Hua Wang, Cheng Deng, Hao Zhang, Xinbo Gao, Heng Huang:
Drosophila Gene Expression Pattern Annotations via Multi-Instance Biological Relevance Learning. AAAI 2016: 1324-1330 - [c45]Feiping Nie, Hua Wang, Cheng Deng, Xinbo Gao, Xuelong Li, Heng Huang:
New l1-Norm Relaxations and Optimizations for Graph Clustering. AAAI 2016: 1962-1968 - [c44]Xue Yang, Fei Han, Hua Wang, Hao Zhang:
Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking. IJCAI 2016: 3522-3529 - [c43]Hao Zhang, Fei Han, Hua Wang:
Robust Multimodal Sequence-Based Loop Closure Detection via Structured Sparsity. Robotics: Science and Systems 2016 - [i1]Xue Yang, Fei Han, Hua Wang, Hao Zhang:
Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking. CoRR abs/1605.00170 (2016) - 2015
- [j12]Hua Wang, Heng Huang, Chris H. Q. Ding:
Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency. J. Comput. Biol. 22(6): 546-562 (2015) - [j11]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Joint Schatten p-norm and ℓp-norm robust matrix completion for missing value recovery. Knowl. Inf. Syst. 42(3): 525-544 (2015) - [j10]Hua Wang, Feiping Nie, Heng Huang:
Large-Scale Cross-Language Web Page Classification via Dual Knowledge Transfer Using Fast Nonnegative Matrix Trifactorization. ACM Trans. Knowl. Discov. Data 10(1): 1:1-1:29 (2015) - [c42]Hua Wang, Feiping Nie, Heng Huang:
Learning Robust Locality Preserving Projection via p-Order Minimization. AAAI 2015: 3059-3065 - 2014
- [j9]Chenping Hou, Feiping Nie, Hua Wang, Dongyun Yi, Changshui Zhang:
Learning high-dimensional correspondence via manifold learning and local approximation. Neural Comput. Appl. 24(7-8): 1555-1568 (2014) - [j8]Hua Wang, Heng Huang, Monica Basco, Molly Lopez, Fillia Makedon:
Self-taught learning via exponential family sparse coding for cost-effective patient thought record categorization. Pers. Ubiquitous Comput. 18(1): 27-35 (2014) - [j7]Hua Wang, Heng Huang, Fillia Makedon:
Emotion Detection via Discriminant Laplacian Embedding. Univers. Access Inf. Soc. 13(1): 23-31 (2014) - [c41]Hua Wang, Feiping Nie, Heng Huang:
Globally and Locally Consistent Unsupervised Projection. AAAI 2014: 1328-1333 - [c40]Hua Wang, Feiping Nie, Heng Huang:
Low-Rank Tensor Completion with Spatio-Temporal Consistency. AAAI 2014: 2846-2852 - [c39]Hua Wang, Feiping Nie, Heng Huang:
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization. ICML 2014: 1836-1844 - [c38]Hua Wang, Heng Huang, Chris H. Q. Ding:
Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency. RECOMB 2014: 311-325 - 2013
- [j6]Hua Wang, Heng Huang, Chris H. Q. Ding:
Function-Function Correlated Multi-label Protein Function Prediction over Interaction Networks. J. Comput. Biol. 20(4): 322-343 (2013) - [j5]Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie:
Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. J. Comput. Biol. 20(4): 344-358 (2013) - [c37]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine. CVPR 2013: 3097-3102 - [c36]Hua Wang, Feiping Nie, Weidong Cai, Heng Huang:
Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization. ICCV 2013: 1145-1152 - [c35]Hua Wang, Feiping Nie, Heng Huang:
Robust and Discriminative Self-Taught Learning. ICML (3) 2013: 298-306 - [c34]Hua Wang, Feiping Nie, Heng Huang:
Multi-View Clustering and Feature Learning via Structured Sparsity. ICML (3) 2013: 352-360 - [c33]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Adaptive Loss Minimization for Semi-Supervised Elastic Embedding. IJCAI 2013: 1565-1571 - [c32]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Early Active Learning via Robust Representation and Structured Sparsity. IJCAI 2013: 1572-1578 - [c31]Hua Wang, Heng Huang, Chris H. Q. Ding:
Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations. IJCAI 2013: 2049-2056 - 2012
- [j4]Hua Wang, Feiping Nie, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort. Bioinform. 28(2): 229-237 (2012) - [j3]Xiao Cai, Hua Wang, Heng Huang, Chris H. Q. Ding:
Joint stage recognition and anatomical annotation of drosophila gene expression patterns. Bioinform. 28(12): 16-24 (2012) - [j2]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning. Bioinform. 28(12): 127-136 (2012) - [j1]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs. Bioinform. 28(18): 619-625 (2012) - [c30]Hua Wang, Feiping Nie, Heng Huang:
Robust and discriminative distance for Multi-Instance Learning. CVPR 2012: 2919-2924 - [c29]Xiao Cai, Hua Wang, Heng Huang, Chris H. Q. Ding:
Simultaneous Image Classification and Annotation via Biased Random Walk on Tri-relational Graph. ECCV (6) 2012: 823-836 - [c28]Feiping Nie, Hua Wang, Xiao Cai, Heng Huang, Chris H. Q. Ding:
Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization. ICDM 2012: 566-574 - [c27]Hua Wang, Dhiraj Joshi, Jiebo Luo, Heng Huang, Minwoo Park:
Simultaneous Image Annotation and Geo-Tag Prediction via Correlation Guided Multi-task Learning. ISM 2012: 69-72 - [c26]Jingwen Yan, Shannon L. Risacher, Sungeun Kim, Jacqueline C. Simon, Taiyong Li, Jing Wan, Hua Wang, Heng Huang, Andrew J. Saykin, Li Shen:
Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning. MBIA 2012: 1-17 - [c25]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction. NIPS 2012: 1286-1294 - [c24]Hua Wang, Heng Huang, Chris H. Q. Ding:
Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks. RECOMB 2012: 302-313 - [c23]Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie:
Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. RECOMB 2012: 314-325 - 2011
- [c22]Hua Wang, Feiping Nie, Heng Huang:
Learning Instance Specific Distance for Multi-Instance Classification. AAAI 2011: 507-512 - [c21]Hua Wang, Heng Huang, Chris H. Q. Ding:
Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization. CIKM 2011: 279-284 - [c20]Hua Wang, Heng Huang, Chris H. Q. Ding:
Image annotation using bi-relational graph of images and semantic labels. CVPR 2011: 793-800 - [c19]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Dyadic transfer learning for cross-domain image classification. ICCV 2011: 551-556 - [c18]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen:
Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. ICCV 2011: 557-562 - [c17]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Unsupervised and semi-supervised learning via ℓ1-norm graph. ICCV 2011: 2268-2273 - [c16]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation. ICDM 2011: 774-783 - [c15]Feiping Nie, Heng Huang, Chris H. Q. Ding, Dijun Luo, Hua Wang:
Robust Principal Component Analysis with Non-Greedy l1-Norm Maximization. IJCAI 2011: 1433-1438 - [c14]Hua Wang, Feiping Nie, Heng Huang, Fillia Makedon:
Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering. IJCAI 2011: 1553-1558 - [c13]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. MICCAI (3) 2011: 115-123 - [c12]Hua Wang, Feiping Nie, Heng Huang, Yi Yang:
Learning frame relevance for video classification. ACM Multimedia 2011: 1345-1348 - [c11]Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Q. Ding:
Maximum Margin Multi-Instance Learning. NIPS 2011: 1-9 - [c10]Hua Wang, Heng Huang, Monica Basco, Molly Lopez, Fillia Makedon:
Cost effective depression patient thought record categorization via self-taught learning. PETRA 2011: 41 - [c9]Hua Wang, Heng Huang, Feiping Nie, Chris H. Q. Ding:
Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization. SIGIR 2011: 933-942 - 2010
- [c8]Hua Wang, Heng Huang, Chris H. Q. Ding:
Discriminant Laplacian Embedding. AAAI 2010: 618-623 - [c7]Hua Wang, Chris H. Q. Ding, Heng Huang:
Multi-Label Classification: Inconsistency and Class Balanced K-Nearest Neighbor. AAAI 2010: 1264-1266 - [c6]Hua Wang, Chris H. Q. Ding, Heng Huang:
Multi-label Linear Discriminant Analysis. ECCV (6) 2010: 126-139 - [c5]Hua Wang, Heng Huang, Chris H. Q. Ding:
Image Categorization Using Directed Graphs. ECCV (3) 2010: 762-775 - [c4]Hua Wang, Heng Huang, Chris H. Q. Ding:
Multi-label Feature Transform for Image Classifications. ECCV (4) 2010: 793-806 - [c3]Hua Wang, Heng Huang, Yanzi Hu, Mindi Anderson, Pamela Rollins, Fillia Makedon:
Emotion detection via discriminative kernel method. PETRA 2010 - [c2]Hua Wang, Chris H. Q. Ding, Heng Huang:
Directed Graph Learning via High-Order Co-linkage Analysis. ECML/PKDD (3) 2010: 451-466
2000 – 2009
- 2009
- [c1]Hua Wang, Heng Huang, Chris H. Q. Ding:
Image annotation using multi-label correlated Green's function. ICCV 2009: 2029-2034
Coauthor Index
Chris Ding
aka: Chris H. Q. Ding
aka: Chris H. Q. Ding
[j20] [j16] [c60] [c56] [i2] [c48] [j13] [c47] [c46] [c45] [j12] [j11] [j10] [c42] [j8] [j7] [c41] [c40] [c39] [c38] [j6] [j5] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [j4] [j3] [j2] [j1] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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