Shao-Bo Lin | DeepAI

AI Chat

Featured Co-authors

Bo Zhang
226 publications
Min Zhang
214 publications
Di Wang
126 publications
Yuan Yao
99 publications
Yao Wang
89 publications
Lei Shi
71 publications
Shaojie Tang
53 publications
Xin Guo
45 publications
Ding-Xuan Zhou
45 publications
Yu Guang Wang
26 publications
Jinshan Zeng
20 publications

∙ 09/08/2023

Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos

Data silos, mainly caused by privacy and interoperability, significantly...

0 Di Wang, et al. ∙

∙ 08/07/2023

Optimal Approximation and Learning Rates for Deep Convolutional Neural Networks

This paper focuses on approximation and learning performance analysis fo...

0 Shao-Bo Lin, et al. ∙

∙ 07/30/2023

Deep Convolutional Neural Networks with Zero-Padding: Feature Extraction and Learning

This paper studies the performance of deep convolutional neural networks...

0 Zhi Han, et al. ∙

∙ 03/08/2023

Sketching with Spherical Designs for Noisy Data Fitting on Spheres

This paper proposes a sketching strategy based on spherical designs, whi...

0 Shao-Bo Lin, et al. ∙

∙ 02/21/2023

Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes

In recent years, large amounts of electronic health records (EHRs) conce...

0 Di Wang, et al. ∙

∙ 12/05/2021

Radial Basis Function Approximation with Distributively Stored Data on Spheres

This paper proposes a distributed weighted regularized least squares alg...

0 Han Feng, et al. ∙

∙ 11/28/2021

Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets

In this paper, we study the generalization performance of global minima ...

0 Shao-Bo Lin, et al. ∙

∙ 11/13/2021

Nyström Regularization for Time Series Forecasting

This paper focuses on learning rate analysis of Nyström regularization w...

0 Zirui Sun, et al. ∙

∙ 06/23/2021

Universal Consistency of Deep Convolutional Neural Networks

Compared with avid research activities of deep convolutional neural netw...

0 Shao-Bo Lin, et al. ∙

∙ 09/16/2020

Kernel-based L_2-Boosting with Structure Constraints

Developing efficient kernel methods for regression is very popular in th...

0 Yao Wang, et al. ∙

∙ 09/03/2020

Kernel Interpolation of High Dimensional Scattered Data

Data sites selected from modeling high-dimensional problems often appear...

0 Shao-Bo Lin, et al. ∙

∙ 04/01/2020

Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization

Deep learning is recognized to be capable of discovering deep features f...

0 Zhi Han, et al. ∙

∙ 04/01/2020

Fully-Corrective Gradient Boosting with Squared Hinge: Fast Learning Rates and Early Stopping

Boosting is a well-known method for improving the accuracy of weak learn...

0 Jinshan Zeng, et al. ∙

∙ 03/27/2020

Distributed Kernel Ridge Regression with Communications

This paper focuses on generalization performance analysis for distribute...

1 Shao-Bo Lin, et al. ∙

∙ 02/10/2020

Distributed Learning with Dependent Samples

This paper focuses on learning rate analysis of distributed kernel ridge...

0 Shao-Bo Lin, et al. ∙

∙ 01/09/2020

Adaptive Stopping Rule for Kernel-based Gradient Descent Algorithms

In this paper, we propose an adaptive stopping rule for kernel-based gra...

0 Xiangyu Chang, et al. ∙

∙ 12/16/2019

Realization of spatial sparseness by deep ReLU nets with massive data

The great success of deep learning poses urgent challenges for understan...

16 Charles K. Chui, et al. ∙

∙ 11/24/2019

Fast Polynomial Kernel Classification for Massive Data

In the era of big data, it is highly desired to develop efficient machin...

0 Jinshan Zeng, et al. ∙

∙ 10/06/2019

Distributed filtered hyperinterpolation for noisy data on the sphere

Problems in astrophysics, space weather research and geophysics usually ...

0 Shao-Bo Lin, et al. ∙

∙ 04/03/2019

Deep Neural Networks for Rotation-Invariance Approximation and Learning

Based on the tree architecture, the objective of this paper is to design...

0 Charles K. Chui, et al. ∙

∙ 02/06/2019

A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning

Efficient training of deep neural networks (DNNs) is a challenge due to ...

0 Jinshan Zeng, et al. ∙

∙ 01/01/2019

Realizing data features by deep nets

This paper considers the power of deep neural networks (deep nets for sh...

0 Zheng-Chu Guo, et al. ∙

∙ 03/10/2018

Generalization and Expressivity for Deep Nets

Along with the rapid development of deep learning in practice, the theor...

0 Shao-Bo Lin, et al. ∙

∙ 03/09/2018

Construction of neural networks for realization of localized deep learning

The subject of deep learning has recently attracted users of machine lea...

0 Charles K. Chui, et al. ∙

∙ 02/28/2017

Learning rates for classification with Gaussian kernels

This paper aims at refined error analysis for binary classification usin...

0 Shao-Bo Lin, et al. ∙

∙ 08/11/2016

Distributed learning with regularized least squares

We study distributed learning with the least squares regularization sche...

0 Shao-Bo Lin, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world