Shao-Bo Lin - RankMe

60 papers A* 1Journal 59

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Cross-Validation: Adaptive Parameter Selection for Kernel-Based Gradient Descents. CoRR Xiaotong Liu, Yunwen Lei, Xiangyu Chang, Shao-Bo Lin
2026	J	`jnl`	Towards Accurate and Interpretable Time-series Forecasting: A Polynomial Learning Approach. CoRR Bo Liu, Shao-Bo Lin, Changmiao Wang, Xiaotong Liu
2026	J	`jnl`	Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction. CoRR Xiaotong Liu, Shao-Bo Lin, Jun Fan, Ding-Xuan Zhou
2025	J	`jnl`	Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos. J. Mach. Learn. Res. Shao-Bo Lin, Xiaotong Liu, Di Wang, Hai Zhang, Ding-Xuan Zhou
2025	J	`jnl`	Balancing Interpretability and Performance in Reinforcement Learning: An Adaptive Spectral Based Linear Approach. CoRR Qianxin Yi, Shao-Bo Lin, Jun Fan, Yao Wang
2025	J	`jnl`	Distributed uncertainty quantification of kernel interpolation on spheres. Math. Comput. Shao-Bo Lin, Xingping Sun, Di Wang
2025	J	`jnl`	Feature Qualification by Deep Nets: A Constructive Approach. CoRR Feilong Cao, Shao-Bo Lin
2025	J	`jnl`	Generalization Performance of Empirical Risk Minimization on Over-Parameterized Deep ReLU Nets. IEEE Trans. Inf. Theory Shao-Bo Lin, Yao Wang, Ding-Xuan Zhou
2025	J	`jnl`	Kernel-based L_2-Boosting with Structure Constraints. J. Mach. Learn. Res. Yao Wang, Xin Guo, Shao-Bo Lin
2025	J	`jnl`	Non-Rival Data as Rival Products: An Encapsulation-Forging Approach for Data Synthesis. CoRR Kaidong Wang, Jiale Li, Shao-Bo Lin, Yao Wang
2025	J	`jnl`	Striking the Perfect Balance: Preserving Privacy While Boosting Utility in Collaborative Medical Prediction Platforms. CoRR Shao-Bo Lin, Xiaotong Liu, Yao Wang
2024	J	`jnl`	Component-based Sketching for Deep ReLU Nets. CoRR Di Wang, Shao-Bo Lin, Deyu Meng, Feilong Cao
2024	J	`jnl`	Integral Operator Approaches for Scattered Data Fitting on Spheres. CoRR Shao-Bo Lin
2024	J	`jnl`	Kernel Interpolation of High Dimensional Scattered Data. SIAM J. Numer. Anal. Shao-Bo Lin, Xiangyu Chang, Xingping Sun
2024	J	`jnl`	Lepskii Principle for Distributed Kernel Ridge Regression. CoRR Shao-Bo Lin
2024	J	`jnl`	Sketching with Spherical Designs for Noisy Data Fitting on Spheres. SIAM J. Sci. Comput. Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
2024	J	`jnl`	Weighted Spectral Filters for Kernel Interpolation on Spheres: Estimates of Prediction Accuracy for Noisy Data. CoRR Xiaotong Liu, Jinxin Wang, Di Wang, Shao-Bo Lin
2024	J	`jnl`	Weighted Spectral Filters for Kernel Interpolation on Spheres: Estimates of Prediction Accuracy for Noisy Data. SIAM J. Imaging Sci. Xiaotong Liu, Jinxin Wang, Di Wang, Shao-Bo Lin
2023	J	`jnl`	Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos. CoRR Di Wang, Xiaotong Liu, Shao-Bo Lin, Ding-Xuan Zhou
2023	J	`jnl`	Adaptive Parameter Selection for Kernel Ridge Regression. CoRR Shao-Bo Lin
2023	J	`jnl`	Construction of Deep ReLU Nets for Spatially Sparse Learning. IEEE Trans. Neural Networks Learn. Syst. Xia Liu, Di Wang, Shao-Bo Lin
2023	J	`jnl`	Deep Convolutional Neural Networks with Zero-Padding: Feature Extraction and Learning. CoRR Zhi Han, Baichen Liu, Shao-Bo Lin, Ding-Xuan Zhou
2023	J	`jnl`	Distributed Uncertainty Quantification of Kernel Interpolation on Spheres. CoRR Shao-Bo Lin, Xingping Sun, Di Wang
2023	J	`jnl`	Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes. CoRR Di Wang, Yao Wang, Shaojie Tang, Shao-Bo Lin
2023	J	`jnl`	Lifting the Veil: Unlocking the Power of Depth in Q-learning. CoRR Shao-Bo Lin, Tao Li, Shaojie Tang, Yao Wang, Ding-Xuan Zhou
2023	J	`jnl`	Optimal Approximation and Learning Rates for Deep Convolutional Neural Networks. CoRR Shao-Bo Lin
2022	J	`jnl`	Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization. IEEE Trans. Pattern Anal. Mach. Intell. Zhi Han, Siquan Yu, Shao-Bo Lin, Ding-Xuan Zhou
2022	J	`jnl`	Distributed Learning With Dependent Samples. IEEE Trans. Inf. Theory Zirui Sun, Shao-Bo Lin
2022	J	`jnl`	Fully corrective gradient boosting with squared hinge: Fast learning rates and early stopping. Neural Networks Jinshan Zeng, Min Zhang, Shao-Bo Lin
2022	J	`jnl`	Learning With Selected Features. IEEE Trans. Cybern. Shao-Bo Lin, Jian Fang, Xiangyu Chang
2022	J	`jnl`	Nystrom Regularization for Time Series Forecasting. J. Mach. Learn. Res. Zirui Sun, Mingwei Dai, Yao Wang, Shao-Bo Lin
2022	J	`jnl`	Realization of Spatial Sparseness by Deep ReLU Nets With Massive Data. IEEE Trans. Neural Networks Learn. Syst. Charles K. Chui, Shao-Bo Lin, Bo Zhang, Ding-Xuan Zhou
2022	J	`jnl`	Toward Efficient Ensemble Learning with Structure Constraints: Convergent Algorithms and Applications. INFORMS J. Comput. Shao-Bo Lin, Shaojie Tang, Yao Wang, Di Wang
2022	J	`jnl`	Universal Consistency of Deep Convolutional Neural Networks. IEEE Trans. Inf. Theory Shao-Bo Lin, Kaidong Wang, Yao Wang, Ding-Xuan Zhou
2021	J	`jnl`	Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets. CoRR Shao-Bo Lin, Yao Wang, Ding-Xuan Zhou
2021	J	`jnl`	Nyström Regularization for Time Series Forecasting. CoRR Zirui Sun, Mingwei Dai, Yao Wang, Shao-Bo Lin
2021	J	`jnl`	On ADMM in Deep Learning: Convergence and Saturation-Avoidance. J. Mach. Learn. Res. Jinshan Zeng, Shao-Bo Lin, Yuan Yao, Ding-Xuan Zhou
2021	J	`jnl`	Radial Basis Function Approximation with Distributively Stored Data on Spheres. CoRR Han Feng, Shao-Bo Lin, Ding-Xuan Zhou
2021	J	`jnl`	Random Sketching for Neural Networks With ReLU. IEEE Trans. Neural Networks Learn. Syst. Di Wang, Jinshan Zeng, Shao-Bo Lin
2021	J	`jnl`	Universal Consistency of Deep Convolutional Neural Networks. CoRR Shao-Bo Lin, Kaidong Wang, Yao Wang, Ding-Xuan Zhou
2020	J	`jnl`	Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization. CoRR Zhi Han, Siquan Yu, Shao-Bo Lin, Ding-Xuan Zhou
2020	J	`jnl`	Distributed Kernel Ridge Regression with Communications. CoRR Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
2020	J	`jnl`	Distributed Kernel Ridge Regression with Communications. J. Mach. Learn. Res. Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
2020	J	`jnl`	Distributed Learning with Dependent Samples. CoRR Shao-Bo Lin
2020	J	`jnl`	Fully-Corrective Gradient Boosting with Squared Hinge: Fast Learning Rates and Early Stopping. CoRR Jinshan Zeng, Min Zhang, Shao-Bo Lin
2020	J	`jnl`	Kernel Interpolation of High Dimensional Scattered Data. CoRR Shao-Bo Lin, Xiangyu Chang, Xingping Sun
2020	J	`jnl`	Kernel-based L_2-Boosting with Structure Constraints. CoRR Yao Wang, Xin Guo, Shao-Bo Lin
2020	J	`jnl`	Realizing Data Features by Deep Nets. IEEE Trans. Neural Networks Learn. Syst. Zheng-Chu Guo, Lei Shi, Shao-Bo Lin
2019	J	`jnl`	Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping. J. Mach. Learn. Res. Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou
2019	J	`jnl`	Deep Net Tree Structure for Balance of Capacity and Approximation Ability. Frontiers Appl. Math. Stat. Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou
2019	J	`jnl`	Deep Neural Networks for Rotation-Invariance Approximation and Learning. CoRR Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou
2019	J	`jnl`	Distributed filtered hyperinterpolation for noisy data on the sphere. CoRR Shao-Bo Lin, Yu Guang Wang, Ding-Xuan Zhou
2019	J	`jnl`	Fast Polynomial Kernel Classification for Massive Data. CoRR Jinshan Zeng, Minrun Wu, Shao-Bo Lin, Ding-Xuan Zhou
2019	J	`jnl`	Generalization and Expressivity for Deep Nets. IEEE Trans. Neural Networks Learn. Syst. Shao-Bo Lin
2019	J	`jnl`	Nonparametric regression using needlet kernels for spherical data. J. Complex. Shao-Bo Lin
2019	J	`jnl`	Realization of spatial sparseness by deep ReLU nets with massive data. CoRR Charles K. Chui, Shao-Bo Lin, Bo Zhang, Ding-Xuan Zhou
2019	J	`jnl`	Realizing data features by deep nets. CoRR Zheng-Chu Guo, Lei Shi, Shao-Bo Lin
2018	J	`jnl`	Construction of Neural Networks for Realization of Localized Deep Learning. Frontiers Appl. Math. Stat. Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou
2018	A*	`conf`	Generalization Bounds for Regularized Pairwise Learning. IJCAI Yunwen Lei, Shao-Bo Lin, Ke Tang
2018	J	`jnl`	Generalization and Expressivity for Deep Nets. CoRR Shao-Bo Lin