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Feilong Cao
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2020 – today
- 2025
- [j143]Dansheng Yu, Feilong Cao
:
Construction and approximation rate for feedforward neural network operators with sigmoidal functions. J. Comput. Appl. Math. 453: 116150 (2025) - 2024
- [j142]Lingpeng Wang, Bing Yang, Hailiang Ye, Feilong Cao
Two-view point cloud registration network: feature and geometry. Appl. Intell. 54(4): 3135-3151 (2024) - [j141]Feilong Cao
Hierarchical structural graph neural network with local relation enhancement for hyperspectral image classification. Digit. Signal Process. 146: 104392 (2024) - [j140]Rui Hu
A novel Complementary Dual-aware Network for point cloud classification. Eng. Appl. Artif. Intell. 137: 109224 (2024) - [j139]Qiuhui Chen
A new matrix representation for the Heisenberg group. Int. J. Wavelets Multiresolution Inf. Process. 22(4): 2450007:1-2450007:15 (2024) - [j138]Feilong Cao, Lei Zhu, Hailiang Ye
A new method for point cloud registration: Adaptive relation-oriented convolution and recurrent correspondence-walk. Knowl. Based Syst. 284: 111280 (2024) - [j137]Feilong Cao, Qiyang Chen
An effective targeted label adversarial attack on graph neural networks by strategically allocating the attack budget. Knowl. Based Syst. 293: 111689 (2024) - [j136]Siqi Liu, Hailiang Ye
A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation. Medical Biol. Eng. Comput. 62(2): 537-549 (2024) - [j135]Xinhong Meng, Xinyu Lu, Hailiang Ye, Bing Yang
A new self-augment CNN for 3D point cloud classification and segmentation. Int. J. Mach. Learn. Cybern. 15(3): 807-818 (2024) - [j134]Sihui Li, Duo Li, Rui Zhang
A novel autism spectrum disorder identification method: spectral graph network with brain-population graph structure joint learning. Int. J. Mach. Learn. Cybern. 15(4): 1517-1532 (2024) - [j133]Kaixuan Yao, Zijin Du, Ming Li, Feilong Cao, Jiye Liang:
Robust graph neural networks with Dirichlet regularization and residual connection. Int. J. Mach. Learn. Cybern. 15(9): 3733-3743 (2024) - [j132]Chenghao Fang, Bing Yang, Hailiang Ye, Feilong Cao
Fast point completion network. Neural Comput. Appl. 36(18): 10897-10913 (2024) - [j131]Tiantian Zhou, Hailiang Ye, Feilong Cao
Node-personalized multi-graph convolutional networks for recommendation. Neural Networks 173: 106169 (2024) - [j130]Feilong Cao
SharpGConv: A Novel Graph Method With Plug-and-Play Sharpening Convolution for Point Cloud Registration. IEEE Trans. Circuits Syst. Video Technol. 34(8): 7095-7105 (2024) - [j129]Qingting Jiang
Label-Decoupled Medical Image Segmentation With Spatial-Channel Graph Convolution and Dual Attention Enhancement. IEEE J. Biomed. Health Informatics 28(5): 2830-2841 (2024) - [j128]Zijin Du
A Novel Local-Global Graph Convolutional Method for Point Cloud Semantic Segmentation. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4798-4812 (2024) - [j127]Feilong Cao
A New Strategy of Graph Structure Attack: Multi-View Perturbation Candidate Edge Learning. IEEE Trans. Netw. Sci. Eng. 11(5): 4158-4168 (2024) - [i3]Di Wang, Shao-Bo Lin, Deyu Meng, Feilong Cao:
Component-based Sketching for Deep ReLU Nets. CoRR abs/2409.14174 (2024) - 2023
- [j126]Min Xiang, Hailiang Ye, Bing Yang
Multi-space and detail-supplemented attention network for point cloud completion. Appl. Intell. 53(12): 14971-14985 (2023) - [j125]Feilong Cao
A dynamic graph aggregation framework for 3D point cloud registration. Eng. Appl. Artif. Intell. 120: 105817 (2023) - [j124]Xinru Shao, Hailiang Ye, Bing Yang
Two-stream coupling network with bidirectional interaction between structure and texture for image inpainting. Expert Syst. Appl. 231: 120700 (2023) - [j123]Jiatong Shi, Hailiang Ye, Bing Yang
An iteration-based interactive attention network for 3D point cloud registration. Neurocomputing 560: 126822 (2023) - [j122]Xinhong Meng, Jinyao Yan, Hailiang Ye, Feilong Cao
Construction and approximation for a class of feedforward neural networks with sigmoidal function. Int. J. Wavelets Multiresolution Inf. Process. 21(6) (2023) - [j121]Hailiang Ye, Yuzhi Song, Ming Li
A new deep graph attention approach with influence and preference relationship reconstruction for rate prediction recommendation. Inf. Process. Manag. 60(5): 103439 (2023) - [j120]Xinhong Meng, Lei Zhu, Hailiang Ye, Feilong Cao:
A new method for two-stage partial-to-partial 3D point cloud registration: multi-level interaction perception. Int. J. Mach. Learn. Cybern. 14(11): 3765-3781 (2023) - [j119]Mingwen Shao, Huan Liu
Adaptive one-stage generative adversarial network for unpaired image super-resolution. Neural Comput. Appl. 35(28): 20909-20922 (2023) - [j118]Jiaxing Miao
Revisiting graph neural networks from hybrid regularized graph signal reconstruction. Neural Networks 157: 444-459 (2023) - [j117]Huan Liu, Mingwen Shao
Image Super-Resolution Using a Simple Transformer Without Pretraining. Neural Process. Lett. 55(2): 1479-1497 (2023) - [j116]Changqin Huang
Are Graph Convolutional Networks With Random Weights Feasible? IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2751-2768 (2023) - [j115]Jiye Liang
Long and Short-Range Dependency Graph Structure Learning Framework on Point Cloud. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14975-14989 (2023) - [j114]Jiaxing Miao
Triplet teaching graph contrastive networks with self-evolving adaptive augmentation. Pattern Recognit. 142: 109687 (2023) - [j113]Bing Yang
GoLoG: Global-to-Local Decoupling Graph Network With Joint Optimization for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 61: 1-14 (2023) - [c28]Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang:
How Powerful are Shallow Neural Networks with Bandlimited Random Weights? ICML 2023: 19960-19981 - [c27]Xinhong Meng, Meng Hu, Hailiang Ye, Ming Li, Feilong Cao:
A Global-and-Local Feature Fusion Network for Point Cloud Classification. ICMLC 2023: 89-96 - 2022
- [j112]Kaixuan Yao
Multi-view graph convolutional networks with attention mechanism. Artif. Intell. 307: 103708 (2022) - [j111]Yi Wang, Hailiang Ye, Feilong Cao
A novel multi-discriminator deep network for image segmentation. Appl. Intell. 52(1): 1092-1109 (2022) - [j110]Yuzhi Song, Hailiang Ye, Ming Li
Deep multi-graph neural networks with attention fusion for recommendation. Expert Syst. Appl. 191: 116240 (2022) - [j109]Jinyao Yan, Xinhong Meng, Feilong Cao, Hailiang Ye
A universal rank approximation method for matrix completion. Int. J. Wavelets Multiresolution Inf. Process. 20(5): 2250016:1-2250016:24 (2022) - [j108]Rui Hu
Decouple the object: Component-level semantic recognizer for point clouds classification. Knowl. Based Syst. 248: 108887 (2022) - [j107]Hangkun Wang
A novel method for point cloud completion: Adaptive region shape fusion network. Knowl. Based Syst. 255: 109770 (2022) - [j106]Feilong Cao, Chengling Gao
A novel method for image segmentation: two-stage decoding network with boundary attention. Int. J. Mach. Learn. Cybern. 13(5): 1461-1473 (2022) - [j105]Chenglin Wen, Tingting Huai, Qinghua Zhang, Zhihuan Song, Feilong Cao:
A new rotation forest ensemble algorithm. Int. J. Mach. Learn. Cybern. 13(11): 3569-3576 (2022) - [j104]Wenhui Guo, Hailiang Ye
Feature-Grouped Network With Spectral-Spatial Connected Attention for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 60: 1-13 (2022) - [j103]Bing Yang
A Novel Method for Hyperspectral Image Classification: Deep Network With Adaptive Graph Structure Integration. IEEE Trans. Geosci. Remote. Sens. 60: 1-12 (2022) - 2021
- [j102]Meng Hu, Hailiang Ye, Feilong Cao
Convolutional neural networks with hybrid weights for 3D point cloud classification. Appl. Intell. 51(10): 6983-6996 (2021) - [j101]Feilong Cao
Consensus-based distributed learning for robust convex optimization with a scenario approach. Concurr. Comput. Pract. Exp. 33(8) (2021) - [j100]Feilong Cao, Baijie Chen:
Densely connected network with improved pyramidal bottleneck residual units for super-resolution. J. Vis. Commun. Image Represent. 74: 102963 (2021) - [j99]Chengling Gao, Hailiang Ye
Multiscale fused network with additive channel-spatial attention for image segmentation. Knowl. Based Syst. 214: 106754 (2021) - [j98]Zijin Du
3D mixed CNNs with edge-point feature learning. Knowl. Based Syst. 221: 106985 (2021) - [j97]Jie Ren, Qimin Zhang
A stochastic age-structured HIV/AIDS model based on parameters estimation and its numerical calculation. Math. Comput. Simul. 190: 159-180 (2021) - [j96]Chenglin Wen, Wenchao Qian, Qinghua Zhang, Feilong Cao:
Algorithms of matrix recovery based on truncated Schatten p-norm. Int. J. Mach. Learn. Cybern. 12(5): 1557-1570 (2021) - [j95]Baiyu Pan
An automatic 2D to 3D video conversion approach based on RGB-D images. Multim. Tools Appl. 80(13): 19179-19201 (2021) - [j94]Hailiang Ye, Zijin Du
A novel 3D shape classification algorithm: point-to-vector capsule network. Neural Comput. Appl. 33(23): 16315-16328 (2021) - [j93]Hailiang Ye
A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer. Neural Networks 144: 755-765 (2021) - [j92]Kaixuan Yao
Deep neural network compression through interpretability-based filter pruning. Pattern Recognit. 119: 108056 (2021) - [j91]Chen Pan
Salient Object Detection Based on Visual Perceptual Saturation and Two-Stream Hybrid Networks. IEEE Trans. Image Process. 30: 4773-4787 (2021) - 2020
- [j90]Hailiang Ye, Feilong Cao
A hybrid regularization approach for random vector functional-link networks. Expert Syst. Appl. 140 (2020) - [j89]Xuejun Wang, Feilong Cao, Wenjian Wang:
Adaptive sparse and dense hybrid representation with nonconvex optimization. Frontiers Comput. Sci. 14(4): 144306 (2020) - [j88]Jianwei Zhao, Taoye Huang, Zhenghua Zhou, Feilong Cao
A Compact Recursive Dense Convolutional Network for image classification. Neurocomputing 372: 8-16 (2020) - [j87]Feilong Cao
Deep hybrid dilated residual networks for hyperspectral image classification. Neurocomputing 384: 170-181 (2020) - [j86]Jie Ren, Qimin Zhang
Modeling a stochastic age-structured capital system with Poisson jumps using neural networks. Inf. Sci. 516: 254-265 (2020) - [j85]Feilong Cao, Wenhui Guo:
Cascaded dual-scale crossover network for hyperspectral image classification. Knowl. Based Syst. 189 (2020) - [j84]Huan Liu, Feilong Cao, Chenglin Wen, Qinghua Zhang:
Lightweight multi-scale residual networks with attention for image super-resolution. Knowl. Based Syst. 203: 106103 (2020) - [j83]Huan Liu, Feilong Cao
Improved dual-scale residual network for image super-resolution. Neural Networks 132: 84-95 (2020) - [j82]Feilong Cao
Deconvolutional neural network for image super-resolution. Neural Networks 132: 394-404 (2020) - [i2]Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang:
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR abs/2008.08427 (2020)
2010 – 2019
- 2019
- [j81]Feilong Cao
Single image super-resolution via multi-scale residual channel attention network. Neurocomputing 358: 424-436 (2019) - [j80]Jianwei Zhao, Chen Chen, Zhenghua Zhou, Feilong Cao
Single image super-resolution based on adaptive convolutional sparse coding and convolutional neural networks. J. Vis. Commun. Image Represent. 58: 651-661 (2019) - [j79]Feilong Cao, Baijie Chen:
New architecture of deep recursive convolution networks for super-resolution. Knowl. Based Syst. 178: 98-110 (2019) - [j78]Wenchao Qian, Feilong Cao
Adaptive algorithms for low-rank and sparse matrix recovery with truncated nuclear norm. Int. J. Mach. Learn. Cybern. 10(6): 1341-1355 (2019) - [j77]Feilong Cao, Yuehua Liu, Zhen Huang, Jianjun Chu, Jianwei Zhao:
Effective segmentations in white blood cell images using ϵ -SVR-based detection method. Neural Comput. Appl. 31(10): 6767-6780 (2019) - [j76]Keqiuyin Li
Super-resolution using neighbourhood regression with local structure prior. Signal Process. Image Commun. 72: 58-68 (2019) - [j75]Hailiang Ye
A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images. IEEE Trans. Geosci. Remote. Sens. 57(7): 4457-4469 (2019) - [j74]Hailiang Ye
A Hybrid Truncated Norm Regularization Method for Matrix Completion. IEEE Trans. Image Process. 28(10): 5171-5186 (2019) - 2018
- [j73]Hailiang Ye, Feilong Cao
Building feedforward neural networks with random weights for large scale datasets. Expert Syst. Appl. 106: 233-243 (2018) - [j72]Jianwei Zhao, Tiantian Sun, Feilong Cao:
Image super-resolution via adaptive sparse representation and self-learning. IET Comput. Vis. 12(5): 753-761 (2018) - [j71]Feilong Cao
Efficient saliency detection using convolutional neural networks with feature selection. Inf. Sci. 456: 34-49 (2018) - [j70]Zhebin Gu, Feilong Cao:
多层前向人工神经网络图像分类算法 (Algorithm of Multi-layer Forward Artificial Neural Network for Image Classification). 计算机科学 45(11A): 238-243 (2018) - [j69]Feilong Cao
A new method for image super-resolution with multi-channel constraints. Knowl. Based Syst. 146: 118-128 (2018) - [j68]Jianwei Zhao, Weidong Zhang, Feilong Cao:
Robust object tracking using a sparse coadjutant observation model. Multim. Tools Appl. 77(23): 30969-30991 (2018) - [j67]Qingguo Chen, Feilong Cao
Distributed support vector machine in master-slave mode. Neural Networks 101: 94-100 (2018) - [j66]Hanchi Ying
Sparsity-Based Spatiotemporal Fusion via Adaptive Multi-Band Constraints. Remote. Sens. 10(10): 1646 (2018) - 2017
- [j65]Jianwei Zhao, Heping Hu, Zhenghua Zhou, Feilong Cao:
Super-resolution reconstruction: using non-local structure similarity and edge sharpness dictionary. IET Image Process. 11(12): 1254-1264 (2017) - [j64]Feilong Cao, Xinshan Feng, Jianwei Zhao:
Sparse representation for robust face recognition by dictionary decomposition. J. Vis. Commun. Image Represent. 46: 260-268 (2017) - [j63]Jianwei Zhao, Heping Hu, Feilong Cao:
Image super-resolution via adaptive sparse representation. Knowl. Based Syst. 124: 23-33 (2017) - [j62]Jianwei Zhao, Minshu Zhang, Zhenghua Zhou, Jianjun Chu, Feilong Cao:
Automatic detection and classification of leukocytes using convolutional neural networks. Medical Biol. Eng. Comput. 55(8): 1287-1301 (2017) - [j61]Feilong Cao, MiaoMiao Cai, Jianjun Chu, Jianwei Zhao, Zhenghua Zhou:
A novel segmentation algorithm for nucleus in white blood cells based on low-rank representation. Neural Comput. Appl. 28(S-1): 503-511 (2017) - [j60]Feilong Cao
Recovering low-rank and sparse matrix based on the truncated nuclear norm. Neural Networks 85: 10-20 (2017) - [j59]Jianwei Zhao, Yongbiao Lv, Zhenghua Zhou, Feilong Cao
A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network. Neural Networks 94: 115-124 (2017) - [j58]Jiao Wu
Nonlocaly Multi-Morphological Representation for Image Reconstruction From Compressive Measurements. IEEE Trans. Image Process. 26(12): 5730-5742 (2017) - [j57]Yuehua Liu, Feilong Cao
Segmentation of White Blood Cells Image Using Adaptive Location and Iteration. IEEE J. Biomed. Health Informatics 21(6): 1644-1655 (2017) - [c26]Fan Feng, Feilong Cao:
Consensus-based Parallel Algorithm for Robust Convex Optimization with Scenario Approach in Colored Network. IDEAL 2017: 222-231 - 2016
- [j56]Shaobo Lin, Feilong Cao:
Simultaneous approximation by spherical neural networks. Neurocomputing 175: 348-354 (2016) - [j55]Zhixiang Chen, Feilong Cao
Scattered data approximation by neural networks operators. Neurocomputing 190: 237-242 (2016) - [j54]Feilong Cao, Dianhui Wang, Hou-Ying Zhu
An iterative learning algorithm for feedforward neural networks with random weights. Inf. Sci. 328: 546-557 (2016) - [j53]Feilong Cao
Pose and illumination variable face recognition via sparse representation and illumination dictionary. Knowl. Based Syst. 107: 117-128 (2016) - [j52]Feilong Cao, MiaoMiao Cai, Yuanpeng Tan, Jianwei Zhao:
Image Super-Resolution via Adaptive ℓp (0<p<1) Regularization and Sparse Representation. IEEE Trans. Neural Networks Learn. Syst. 27(7): 1550-1561 (2016) - 2015
- [j51]Zhixiang Chen, Feilong Cao, Jinjie Hu:
Approximation by network operators with logistic activation functions. Appl. Math. Comput. 256: 565-571 (2015) - [j50]Ming Li
Multiscale interpolation on the sphere: Convergence rate and inverse theorem. Appl. Math. Comput. 263: 134-150 (2015) - [j49]Kankan Dai, Jianwei Zhao, Feilong Cao
A novel algorithm of extended neural networks for image recognition. Eng. Appl. Artif. Intell. 42: 57-66 (2015) - [j48]Wanggen Wan, Zhenghua Zhou, Jianwei Zhao, Feilong Cao
A novel face recognition method: Using random weight networks and quasi-singular value decomposition. Neurocomputing 151: 1180-1186 (2015) - [j47]Yuanpeng Tan, Feilong Cao, MiaoMiao Cai:
A New System of Face Recognition: Using Fuzziness and Sparsity. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(6): 829-844 (2015) - [j46]Huaixin Cao, Feilong Cao, Dianhui Wang:
Quantum artificial neural networks with applications. Inf. Sci. 290: 1-6 (2015) - [j45]Huaixin Cao, Dianhui Wang, Feilong Cao:
An adiabatic quantum algorithm and its application to DNA motif model discovery. Inf. Sci. 296: 275-281 (2015) - [j44]Feilong Cao, Hailiang Ye, Dianhui Wang:
A probabilistic learning algorithm for robust modeling using neural networks with random weights. Inf. Sci. 313: 62-78 (2015) - [j43]Zhixiang Chen, Jinjie Hu, Feilong Cao:
Learning Algorithm of Neural Networks on Spherical Cap. J. Networks 10(3): 152-158 (2015) - [j42]Jianwei Zhao, Zhihui Wang
A local learning algorithm for random weights networks. Knowl. Based Syst. 74: 159-166 (2015) - [j41]Kankan Dai, Jianwei Zhao, Feilong Cao:
A novel decorrelated neural network ensemble algorithm for face recognition. Knowl. Based Syst. 89: 541-552 (2015) - [j40]Feilong Cao, MiaoMiao Cai, Yuanpeng Tan:
Image Interpolation via Low-Rank Matrix Completion and Recovery. IEEE Trans. Circuits Syst. Video Technol. 25(8): 1261-1270 (2015) - [c25]Feilong Cao, Jing Lu, Jianjun Chu, Zhenghua Zhou, Jianwei Zhao, Guoqiang Chen:
Leukocyte image segmentation using feed forward neural networks with random weights. ICNC 2015: 736-742 - 2014
- [j39]Zhenghua Zhou, Jianwei Zhao, Feilong Cao:
Diagnosis of fatigue crack growth with recursive random weight networks. Comput. Electr. Eng. 40(7): 2227-2235 (2014) - [j38]Feilong Cao, Yuanpeng Tan, MiaoMiao Cai:
Sparse algorithms of Random Weight Networks and applications. Expert Syst. Appl. 41(5): 2457-2462 (2014) - [j37]Jing Lu, Jianwei Zhao, Feilong Cao:
Extended feed forward neural networks with random weights for face recognition. Neurocomputing 136: 96-102 (2014) - [j36]Zhenghua Zhou, Jianwei Zhao, Feilong Cao:
A novel approach for fault diagnosis of induction motor with invariant character vectors. Inf. Sci. 281: 496-506 (2014) - [j35]Jianwei Zhao, Zhenghua Zhou, Feilong Cao:
Human face recognition based on ensemble of polyharmonic extreme learning machine. Neural Comput. Appl. 24(6): 1317-1326 (2014) - [j34]Feilong Cao, Tenghui Dai, Yongquan Zhang, Yuanpeng Tan:
Compressed classification learning with Markov chain samples. Neural Networks 50: 90-97 (2014) - [j33]Feilong Cao, Yufang Liu, Weiguo Zhang:
Generalization Bounds of Regularization Algorithm with Gaussian Kernels. Neural Process. Lett. 39(2): 179-194 (2014) - [j32]Jianwei Zhao, Zhihui Wang
Extreme learning machine with errors in variables. World Wide Web 17(5): 1205-1216 (2014) - [i1]Yuguang Wang, Feilong Cao, Yubo Yuan:
A study on effectiveness of extreme learning machine. CoRR abs/1409.3924 (2014) - 2013
- [j31]Shaobo Lin, Xiaofei Guo, Feilong Cao, Zongben Xu:
Approximation by neural networks with scattered data. Appl. Math. Comput. 224: 29-35 (2013) - [j30]Feilong Cao, Bo Liu, Dong Sun Park:
Image classification based on effective extreme learning machine. Neurocomputing 102: 90-97 (2013) - [c24]Zhenghua Zhou, Jianwei Zhao, Feilong Cao:
Face Recognition Based on Random Weights Network and Quasi Singular Value Decomposition. ICIC (3) 2013: 136-141 - [c23]Feilong Cao, Jianwei Zhao, Bo Liu:
Fast Image Classification Algorithms Based on Random Weights Networks. ISNN (1) 2013: 547-557 - [c22]Jianwei Zhao, Yanqing Fu, Yuanpeng Tan, Feilong Cao:
A Reduction Algorithm for the Big Data in 3D Surface Reconstruction. SMC 2013: 4843-4847 - 2012
- [j29]Chengye Zhao, Feilong Cao:
The Diameter of Connected Domination Critical Graphs. Ars Comb. 107: 537-541 (2012) - [j28]Zongben Xu, Yongquan Zhang, Feilong Cao:
Estimation of convergence rate for multi-regression learning algorithm. Sci. China Inf. Sci. 55(3): 701-713 (2012) - [j27]Feilong Cao, Xing Xing, Jianwei Zhao:
Learning rates of support vector machine classifier for density level detection. Neurocomputing 82: 84-90 (2012) - [j26]Shaobo Lin, Feilong Cao, Xiangyu Chang, Zongben Xu:
A general radial quasi-interpolation operator on the sphere. J. Approx. Theory 164(10): 1402-1414 (2012) - [j25]Zhixiang Chen, Feilong Cao, Jinjie Hu:
Error estimates of quasi-interpolation and its derivatives. J. Comput. Appl. Math. 236(13): 3137-3146 (2012) - [j24]Yubo Yuan, Hou-Ying Zhu
Software reliability modeling with removed errors and compounded-decreased-rate. Math. Comput. Model. 55(3-4): 697-709 (2012) - [j23]Yongquan Zhang, Feilong Cao, Canwei Yan:
Learning rates of least-square regularized regression with strongly mixing observation. Int. J. Mach. Learn. Cybern. 3(4): 277-283 (2012) - [j22]Yongquan Zhang, Feilong Cao:
Analysis of convergence performance of neural networks ranking algorithm. Neural Networks 34: 65-71 (2012) - [j21]Feilong Cao, Dan Wu, Joonwhoan Lee:
Learning Rates for Regularized Classifiers Using Trigonometric Polynomial Kernels. Neural Process. Lett. 35(3): 265-281 (2012) - [j20]Jianwei Zhao, Dong Sun Park, Joonwhoan Lee
Generalized extreme learning machine acting on a metric space. Soft Comput. 16(9): 1503-1514 (2012) - 2011
- [j19]Chengye Zhao, Yuansheng Yang, Linlin Sun, Feilong Cao:
The Connected Domination and Tree Domination of P(n, k) for k = 1, 2, [n/2]. Ars Comb. 101: 467-479 (2011) - [j18]Tingfan Xie, Feilong Cao:
The errors of simultaneous approximation of multivariate functions by neural networks. Comput. Math. Appl. 61(10): 3146-3152 (2011) - [j17]Yongquan Zhang, Feilong Cao, Zongben Xu:
Optimal rate of the regularized regression learning algorithm. Int. J. Comput. Math. 88(7): 1471-1483 (2011) - [j16]Yongquan Zhang, Feilong Cao, Zongben Xu:
Estimation of learning rate of least square algorithm via Jackson operator. Neurocomputing 74(4): 516-521 (2011) - [j15]Yubo Yuan, Yuguang Wang
Optimization approximation solution for regression problem based on extreme learning machine. Neurocomputing 74(16): 2475-2482 (2011) - [j14]Yuguang Wang
A study on effectiveness of extreme learning machine. Neurocomputing 74(16): 2483-2490 (2011) - [j13]Shaobo Lin, Feilong Cao, Zongben Xu:
Essential rate for approximation by spherical neural networks. Neural Networks 24(7): 752-758 (2011) - [c21]Yubo Yuan, Jing Lu, Feilong Cao:
Baby formula classification based on forth order polynomial smoothing support vector machine. ICMLC 2011: 685-691 - [c20]Hou-Ying Zhu
A novel software reliability model with the decrease-rate of removing errors. ICMLC 2011: 943-949 - 2010
- [j12]Zhixiang Chen, Feilong Cao:
Global errors for approximate approximations with Gaussian kernels on compact intervals. Appl. Math. Comput. 217(2): 725-734 (2010) - [j11]Tingfan Xie, Feilong Cao:
The errors in simultaneous approximation by feed-forward neural networks. Neurocomputing 73(4-6): 903-907 (2010) - [j10]Feilong Cao, Shaobo Lin, Zongben Xu:
Approximation capability of interpolation neural networks. Neurocomputing 74(1-3): 457-460 (2010) - [j9]Feilong Cao, Shaobo Lin, Zongben Xu:
Constructive approximate interpolation by neural networks in the metric space. Math. Comput. Model. 52(9-10): 1674-1681 (2010) - [c19]Qingxiang Fang
Adaptive control of singular nonlinear systems with convex/concave parametrization. ICARCV 2010: 1680-1683 - [c18]Chunmei Ding, Yubo Yuan, Feilong Cao:
Approximation by approximate interpolation neural networks with single hidden layer. ICMLC 2010: 1431-1436 - [c17]Chunmei Ding, Yubo Yuan, Feilong Cao:
Approximate interpolation by a class of neural networks in Lebesgue metric. ICMLC 2010: 3134-3139 - [c16]Yubo Yuan, Feilong Cao:
Canonical duality solution to support vector machine. ICMLC 2010: 3140-3145 - [c15]Dongmei Pu, Yubo Yuan, Feilong Cao:
Estimate human gene family number by improved k-means clustering. ICMLC 2010: 3146-3149 - [c14]Yubo Yuan, Dongmei Pu, Feilong Cao:
Sixth order polynomial smoothing approximation solution to support vector machine. ICMLC 2010: 3154-3157 - [c13]Feilong Cao, Tingfan Xie:
The construction and approximation for feedforword neural networks with fixed weights. ICMLC 2010: 3164-3168 - [c12]Feilong Cao, Yubo Yuan, Chunmei Ding:
Exact and approximate interpolation for neural networks with single hidden layer. ICNC 2010: 273-277 - [c11]Yubo Yuan, Feilong Cao:
A new solution method to support vector machine based on arc smoothing function. ICNC 2010: 828-831 - [c10]Jianwei Zhao, Feilong Cao:
Neural networks for interpolation of functionals on a Hilbert space. ICNC 2010: 1122-1125
2000 – 2009
- 2009
- [j8]Feilong Cao, Yongquan Zhang, Zongben Xu:
Lower estimation of approximation rate for neural networks. Sci. China Ser. F Inf. Sci. 52(8): 1321-1327 (2009) - [j7]Zhixiang Chen, Feilong Cao:
The approximation operators with sigmoidal functions. Comput. Math. Appl. 58(4): 758-765 (2009) - [j6]Feilong Cao, Rui Zhang:
The errors of approximation for feedforward neural networks in the Lp metric. Math. Comput. Model. 49(7-8): 1563-1572 (2009) - [c9]Feilong Cao, Yubo Yuan:
Convergence rates for a class of neural networks with logarithmic function. GrC 2009: 27-32 - [c8]Chen Pan, Huijuan Lu, Feilong Cao:
Segmentation of Blood and Bone Marrow Cell Images via Learning by Sampling. ICIC (1) 2009: 336-345 - [c7]Chen Pan, Feilong Cao:
Marrow Cell Segmentation by Simulating Visual System. ICNC (1) 2009: 189-194 - [c6]Chen Pan, Feilong Cao:
Face Image Recognition Combining Holistic and Local Features. ISNN (3) 2009: 407-415 - 2008
- [j5]Feilong Cao, Tingfan Xie, Zongben Xu:
The estimate for approximation error of neural networks: A constructive approach. Neurocomputing 71(4-6): 626-630 (2008) - [j4]Chunmei Ding, Feilong Cao:
K-functionals and multivariate Bernstein polynomials. J. Approx. Theory 155(2): 125-135 (2008) - [c5]Youmei Li, Zongben Xu, Feilong Cao:
An Improvement to Ant Colony Optimization Heuristic. ISNN (1) 2008: 816-825 - 2007
- [c4]Ruyue Yang, Xing Pan, Feilong Cao:
The Constructive Methods and Numerical Results for Approximation of Neural Networks. ICNC (1) 2007: 320-324 - 2006
- [c3]Chunmei Ding, Feilong Cao, Zongben Xu:
The Essential Approximation Order for Neural Networks with Trigonometric Hidden Layer Units. ISNN (1) 2006: 72-79 - 2005
- [j3]Feilong Cao:
Derivatives of multidimensional Bernstein operators and smoothness. J. Approx. Theory 132(2): 241-257 (2005) - [c2]Feilong Cao, Zongben Xu, Youmei Li:
Pointwise Approximation for Neural Networks. ISNN (1) 2005: 39-44 - [c1]Youmei Li, Zongben Xu, Feilong Cao:
Generalization and Property Analysis of GENET. ISNN (1) 2005: 63-68 - 2004
- [j2]Zongben Xu, Feilong Cao:
The essential order of approximation for neural networks. Sci. China Ser. F Inf. Sci. 47(1): 97-112 (2004) - 2003
- [j1]Ruyue Yang, Jingyi Xiong, Feilong Cao:
Multivariate Stancu operators defined on a simplex. Appl. Math. Comput. 138(2-3): 189-198 (2003)
Coauthor Index
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