Zheng-Chu Guo

According to our database, Zheng-Chu Guo authored at least 25 papers between 2011 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Unbounded Density Ratio Estimation and Its Application to Covariate Shift Adaptation.

Ren-Rui Liu, Jun Fan, Lei Shi, Zheng-Chu Guo

CoRR, March, 2026

2025

Robust kernel-based gradient descent with random features.

Qi Hong, Zheng-Chu Guo

Adv. Comput. Math., December, 2025

Online learning algorithms tackling covariate shift.

Zheng-Chu Guo, Lei Shi

Adv. Comput. Math., December, 2025

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification.

Yuanfan Li, Yunwen Lei, Zheng-Chu Guo, Yiming Ying

CoRR, October, 2025

Spectral Algorithms in Misspecified Regression: Convergence under Covariate Shift.

Ren-Rui Liu, Zheng-Chu Guo

CoRR, September, 2025

Spectral Algorithms under Covariate Shift.

Jun Fan, Zheng-Chu Guo, Lei Shi

CoRR, April, 2025

2024

Optimality of Robust Online Learning.

Zheng-Chu Guo, Andreas Christmann, Lei Shi

Found. Comput. Math., October, 2024

Coefficient-based regularized distribution regression.

Yuan Mao, Lei Shi, Zheng-Chu Guo

J. Approx. Theory, January, 2024

Online regularized learning algorithm for functional data.

Yuan Mao, Zheng-Chu Guo

J. Complex., 2024

Stochastic Gradient Descent for Two-layer Neural Networks.

Dinghao Cao, Zheng-Chu Guo, Lei Shi

CoRR, 2024

2022

Capacity dependent analysis for functional online learning algorithms.

Xin Guo, Zheng-Chu Guo, Lei Shi

CoRR, 2022

2020

Realizing Data Features by Deep Nets.

Zheng-Chu Guo, Lei Shi, Shao-Bo Lin

IEEE Trans. Neural Networks Learn. Syst., 2020

Optimal learning rates for distribution regression.

Zhiying Fang, Zheng-Chu Guo, Ding-Xuan Zhou

J. Complex., 2020

2019

Fast and strong convergence of online learning algorithms.

Zheng-Chu Guo, Lei Shi

Adv. Comput. Math., 2019

2017

Convergence of Unregularized Online Learning Algorithms.

Yunwen Lei, Lei Shi, Zheng-Chu Guo

J. Mach. Learn. Res., 2017

Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network.

Zheng-Chu Guo, Lei Shi, Qiang Wu

J. Mach. Learn. Res., 2017

Online regularized learning with pairwise loss functions.

Zheng-Chu Guo, Yiming Ying, Ding-Xuan Zhou

Adv. Comput. Math., 2017

Learning from Networked Examples.

Yuyi Wang, Zheng-Chu Guo, Jan Ramon

Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016

Generalization bounds for metric and similarity learning.

Qiong Cao, Zheng-Chu Guo, Yiming Ying

Mach. Learn., 2016

2014

Guaranteed Classification via Regularized Similarity Learning.

Zheng-Chu Guo, Yiming Ying

Neural Comput., 2014

2013

Learning from networked examples in a k-partite graph.

Yuyi Wang, Jan Ramon, Zheng-Chu Guo

CoRR, 2013

Concentration estimates for learning with unbounded sampling.

Zheng-Chu Guo, Ding-Xuan Zhou

Adv. Comput. Math., 2013

Learning with coefficient-based regularization and ℓ1 -penalty.

Zheng-Chu Guo, Lei Shi

Adv. Comput. Math., 2013

2011

Classification with non-i.i.d. sampling.

Zheng-Chu Guo, Lei Shi

Math. Comput. Model., 2011

Online regression with unbounded sampling.

Zheng-Chu Guo, Cheng Wang

Int. J. Comput. Math., 2011