Shao-Bo Lin | DeepAI

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∙ 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. ∙

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