Shaobo Lin

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 48

Top Topics

Greedy Algorithm

Gaussian Kernels

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

IEEE Trans. Cybern.

Publications

Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
An Effective Crop-Paste Pipeline for Few-shot Object Detection. CoRR (2023)
Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
An Effective Crop-Paste Pipeline for Few-shot Object Detection. CVPR Workshops (2023)
Shaobo Lin, Xingyu Zeng, Rui Zhao
Explore the Power of Dropout on Few-shot Learning. CoRR (2023)
Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
Explore the Power of Synthetic Data on Few-shot Object Detection. CoRR (2023)
Shaobo Lin, Di Wang, Ding-Xuan Zhou
Sketching with Spherical Designs for Noisy Data Fitting on Spheres. CoRR (2023)
Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
Explore the Power of Synthetic Data on Few-shot Object Detection. CVPR Workshops (2023)
Shaobo Lin, Xingyu Zeng, Shilin Yan, Rui Zhao
Three-stage Training Pipeline with Patch Random Drop for Few-shot Object Detection. ACCV (6) (2022)
Shaobo Lin, Xingyu Zeng, Rui Zhao
A Unified Framework with Meta-dropout for Few-shot Learning. CoRR (2022)
Shaobo Lin, Yuguang Wang, Ding-Xuan Zhou
Distributed Filtered Hyperinterpolation for Noisy Data on the Sphere. SIAM J. Numer. Anal. 59 (2) (2021)
Long Chen, Shaobo Lin, Xiankai Lu, Dongpu Cao, Hangbin Wu, Chi Guo, Chun Liu, Fei-Yue Wang
Deep Neural Network Based Vehicle and Pedestrian Detection for Autonomous Driving: A Survey. IEEE Trans. Intell. Transp. Syst. 22 (6) (2021)
Jian Fang, Shaobo Lin, Zongben Xu
Learning Through Deterministic Assignment of Hidden Parameters. IEEE Trans. Cybern. 50 (5) (2020)
Xiangyu Chang, Yan Zhong, Yao Wang, Shaobo Lin
Unified Low-Rank Matrix Estimate via Penalized Matrix Least Squares Approximation. IEEE Trans. Neural Networks Learn. Syst. 30 (2) (2019)
Shaobo Lin, Jinshan Zeng, Xiaoqin Zhang
Constructive Neural Network Learning. IEEE Trans. Cybern. 49 (1) (2019)
Shaobo Lin, Jinshan Zeng
Fast Learning With Polynomial Kernels. IEEE Trans. Cybern. 49 (10) (2019)
Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
Global Convergence of Block Coordinate Descent in Deep Learning. ICML (2019)
Jinshan Zeng, Shaobo Lin, Yuan Yao
A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning. CoRR (2019)
Yao Wang, Xu Liao, Shaobo Lin
Rescaled Boosting in Classification. IEEE Trans. Neural Networks Learn. Syst. 30 (9) (2019)
Shaobo Lin, Long Chen, Qin Zou, Wei Tian
High-Resolution Driving Scene Synthesis Using Stacked Conditional Gans and Spectral Normalization. ICME (2019)
Lin Xu, Shaobo Lin, Jinshan Zeng, Xia Liu, Yi Fang, Zongben Xu
Greedy Criterion in Orthogonal Greedy Learning. IEEE Trans. Cybern. 48 (3) (2018)
Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
Block Coordinate Descent for Deep Learning: Unified Convergence Guarantees. CoRR (2018)
Jinshan Zeng, Zhimin Peng, Shaobo Lin
regularized least squares regression" [J. Comput. Appl. Math. 319 (2017) 220-235]. J. Comput. Appl. Math. 333 (2018)
Charles K. Chui, Shaobo Lin, Ding-Xuan Zhou
Construction of neural networks for realization of localized deep learning. CoRR (2018)
Jian Fang, Shaobo Lin, Zongben Xu
Learning through deterministic assignment of hidden parameters. CoRR (2018)
Xiangyu Chang, Shaobo Lin, Ding-Xuan Zhou
Distributed Semi-supervised Learning with Kernel Ridge Regression. J. Mach. Learn. Res. 18 (2017)
Shaobo Lin, Jinshan Zeng, Xiangyu Chang
Learning Rates for Classification with Gaussian Kernels. Neural Comput. 29 (12) (2017)
Lin Xu, Shaobo Lin, Yao Wang, Zongben Xu
-Rescale Boosting for Regression. IEEE Trans. Neural Networks Learn. Syst. 28 (8) (2017)
Shaobo Lin, Xin Guo, Ding-Xuan Zhou
Distributed Learning with Regularized Least Squares. J. Mach. Learn. Res. 18 (2017)
Shaobo Lin
Limitations of shallow nets approximation. Neural Networks 94 (2017)
Shaobo Lin, Jinshan Zeng, Xiangyu Chang
Learning rates for classification with Gaussian kernels. CoRR (2017)
Jinshan Zeng, Zhimin Peng, Shaobo Lin
regularized least squares regression. J. Comput. Appl. Math. 319 (2017)
Shaobo Lin
Linear and nonlinear approximation of spherical radial basis function networks. J. Complex. 35 (2016)
Jinshan Zeng, Shaobo Lin, Zongben Xu
Sparse Regularization: Convergence Of Iterative Jumping Thresholding Algorithm. IEEE Trans. Signal Process. 64 (19) (2016)
Shaobo Lin, Feilong Cao
Simultaneous approximation by spherical neural networks. Neurocomputing 175 (2016)
Shaobo Lin, Jinshan Zeng, Xiaoqin Zhang
Constructive neural network learning. CoRR (2016)
Shaobo Lin, Xin Guo, Ding-Xuan Zhou
Distributed Learning with Regularized Least Squares. CoRR (2016)
Lin Xu, Shaobo Lin, Zongben Xu
Learning capability of the truncated greedy algorithm. Sci. China Inf. Sci. 59 (5) (2016)
Lin Xu, Shaobo Lin, Jinshan Zeng, Xia Liu, Zongben Xu
Greedy Criterion in Orthogonal Greedy Learning. CoRR (2016)
Xiangyu Chang, Shaobo Lin, Yao Wang
Divide and Conquer Local Average Regression. CoRR (2016)
Jian Fang, Shaobo Lin, Zongben Xu
Learning and approximation capabilities of orthogonal super greedy algorithm. Knowl. Based Syst. 95 (2016)
Shaobo Lin, Yao Wang, Lin Xu
Re-scale boosting for regression and classification. CoRR (2015)
Shaobo Lin, Xingping Sun, Zongben Xu, Jinshan Zeng
Model selection of polynomial kernel regression. CoRR (2015)
Shaobo Lin
Nonparametric regression using needlet kernels for spherical data. CoRR (2015)
Shaobo Lin, Xia Liu, Jian Fang, Zongben Xu
Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part II). IEEE Trans. Neural Networks Learn. Syst. 26 (1) (2015)
Shaobo Lin, Jinshan Zeng, Lin Xu, Zongben Xu
Jackson-type inequalities for spherical neural networks with doubling weights. Neural Networks 63 (2015)
Shaobo Lin, Jinshan Zeng, Zongben Xu
Error Estimate for Spherical Neural Networks Interpolation. Neural Process. Lett. 42 (2) (2015)
Xia Liu, Shaobo Lin, Jian Fang, Zongben Xu
Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part I). IEEE Trans. Neural Networks Learn. Syst. 26 (1) (2015)
Lin Xu, Shaobo Lin, Yao Wang, Zongben Xu
-re-scale boosting for regression. CoRR (2015)
Jinshan Zeng, Zhimin Peng, Shaobo Lin
A Gauss-Seidel Iterative Thresholding Algorithm for lq Regularized Least Squares Regression. CoRR (2015)
Jinshan Zeng, Shaobo Lin, Zongben Xu
Sparse solution of underdetermined linear equations via adaptively iterative thresholding. Signal Process. 97 (2014)
Lin Xu, Shaobo Lin, Jinshan Zeng, Zongben Xu
Greedy metrics in orthogonal greedy learning. CoRR (2014)
Shaobo Lin, Xia Liu, Jian Fang, Zongben Xu
Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part II). CoRR (2014)
Jian Fang, Shaobo Lin, Zongben Xu
Learning and approximation capability of orthogonal super greedy algorithm. CoRR (2014)
Shaobo Lin, Xia Liu, Yuanhua Rong, Zongben Xu
Almost optimal estimates for approximation and learning by radial basis function networks. Mach. Learn. 95 (2) (2014)
Jinshan Zeng, Shaobo Lin, Yao Wang, Zongben Xu
Regularization: Convergence of Iterative Half Thresholding Algorithm. IEEE Trans. Signal Process. 62 (9) (2014)
Shaobo Lin, Jinshan Zeng, Jian Fang, Zongben Xu
Coefficient Regularization Learning with Gaussian Kernel. Neural Comput. 26 (10) (2014)
Shaobo Lin, Yuanhua Rong, Xingping Sun, Zongben Xu
Learning Capability of Relaxed Greedy Algorithms. IEEE Trans. Neural Networks Learn. Syst. 24 (10) (2013)
Shaobo Lin, Jinshan Zeng, Jian Fang, Zongben Xu
coefficient regularization learning with Gaussian kernel. CoRR (2013)
Jinshan Zeng, Shaobo Lin, Yao Wang, Zongben Xu
Regularization: Convergence of Iterative Half Thresholding Algorithm. CoRR (2013)
Jinshan Zeng, Shaobo Lin, Zongben Xu
Sparse Solution of Underdetermined Linear Equations via Adaptively Iterative Thresholding. CoRR (2013)
Shaobo Lin, Chen Xu, Jinshan Zeng, Jian Fang
regularization learning depend on q? A negative example. CoRR (2013)
Shaobo Lin, Xiaofei Guo, Feilong Cao, Zongben Xu
Approximation by neural networks with scattered data. Appl. Math. Comput. 224 (2013)
Shaobo Lin, Feilong Cao, Xiangyu Chang, Zongben Xu
A general radial quasi-interpolation operator on the sphere. J. Approx. Theory 164 (10) (2012)
Shaobo Lin, Feilong Cao, Zongben Xu
Essential rate for approximation by spherical neural networks. Neural Networks 24 (7) (2011)
Feilong Cao, Shaobo Lin, Zongben Xu
Approximation capability of interpolation neural networks. Neurocomputing 74 (1-3) (2010)
Feilong Cao, Shaobo Lin, Zongben Xu
Constructive approximate interpolation by neural networks in the metric space. Math. Comput. Model. 52 (9-10) (2010)