Shao-Bo Lin
10 papers · 2017–2026 · 2 venues · across top CS/AI venues
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Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory Β· Machine Learning
(8)
Core Methods
(7)
Learning Paradigms
(3)
Learning Types
(3)
Deep Learning
(2)
Mathematics & Optimization
(2)
Architectures
(2)
Optimization
(2)
Optimization & Theory Β· Deep Learning
(2)
Data Science & Analytics
(1)
Application Areas
(1)
Methods
(1)
Keywords
kernel ridge regression
(4)
learning rate
(4)
distributed learning
(4)
kernel methods
(3)
generalization error
(2)
neural network optimization
(1)
privacy preservation
(1)
semi-supervised learning
(1)
regularized learning
(1)
boosting algorithm
(1)
reproducing kernel hilbert space
(1)
time series forecasting
(1)
empirical risk minimization
(1)
privacy-preserving learning
(1)
early stopping
(1)
nonlinear approximation
(1)
kernel learning
(1)
generalization bound
(1)
global convergence
(1)
metric learning
(1)
Papers
Optimal Approximation and Generalization Errors for Deep Convolutional Neural Networks
JMLR 2026
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos
JMLR 2025
Kernel-based L_2-Boosting with Structure Constraints
JMLR 2025
Nystrom Regularization for Time Series Forecasting
JMLR 2022
On ADMM in Deep Learning: Convergence and Saturation-Avoidance
JMLR 2021
Distributed Kernel Ridge Regression with Communications
JMLR 2020
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping
JMLR 2019
Generalization Bounds for Regularized Pairwise Learning
IJCAI 2018
Distributed Learning with Regularized Least Squares
JMLR 2017
Distributed Semi-supervised Learning with Kernel Ridge Regression
JMLR 2017