Peizhong Ju

Peizhong Ju

Purdue University

H-index: 7

North America-United States

About Peizhong Ju

Peizhong Ju, With an exceptional h-index of 7 and a recent h-index of 6 (since 2020), a distinguished researcher at Purdue University, specializes in the field of Machine Learning, Smart Grid, Optimization, Wireless Communication.

His recent articles reflect a diverse array of research interests and contributions to the field:

Non-asymptotic Convergence of Discrete-time Diffusion Models: New Approach and Improved Rate

AI‐EDGE: An NSF AI institute for future edge networks and distributed intelligence

Theoretical characterization of the generalization performance of overfitted meta-learning

Theoretical Analysis on the Generalization Power of Overfitted Transfer Learning

Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning

Understanding the Theoretical Generalization Performance of Federated Learning

Theory on forgetting and generalization of continual learning

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Peizhong Ju Information

University

Position

School of Electrical and Computer Engineering

Citations(all)

130

Citations(since 2020)

112

Cited By

58

hIndex(all)

7

hIndex(since 2020)

6

i10Index(all)

4

i10Index(since 2020)

4

Email

University Profile Page

Google Scholar

Peizhong Ju Skills & Research Interests

Machine Learning

Smart Grid

Optimization

Wireless Communication

Top articles of Peizhong Ju

Non-asymptotic Convergence of Discrete-time Diffusion Models: New Approach and Improved Rate

arXiv preprint arXiv:2402.13901

2024/2/21

Yuchen Liang
Yuchen Liang

H-Index: 2

Peizhong Ju
Peizhong Ju

H-Index: 4

AI‐EDGE: An NSF AI institute for future edge networks and distributed intelligence

AI Magazine

2024/2/10

Peizhong Ju
Peizhong Ju

H-Index: 4

Chengzhang Li
Chengzhang Li

H-Index: 4

Theoretical characterization of the generalization performance of overfitted meta-learning

arXiv preprint arXiv:2304.04312

2023/4/9

Peizhong Ju
Peizhong Ju

H-Index: 4

Theoretical Analysis on the Generalization Power of Overfitted Transfer Learning

2023/10/13

Peizhong Ju
Peizhong Ju

H-Index: 4

Sen Lin
Sen Lin

H-Index: 3

Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning

2023/10/13

Peizhong Ju
Peizhong Ju

H-Index: 4

Arnob Ghosh
Arnob Ghosh

H-Index: 11

Understanding the Theoretical Generalization Performance of Federated Learning

2023/10/13

Theory on forgetting and generalization of continual learning

2023/7/3

Sen Lin
Sen Lin

H-Index: 3

Peizhong Ju
Peizhong Ju

H-Index: 4

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

arXiv preprint arXiv:2306.12981

2023/6/22

Yining Li
Yining Li

H-Index: 1

Peizhong Ju
Peizhong Ju

H-Index: 4

Generalization Performance of Transfer Learning: Overparameterized and Underparameterized Regimes

arXiv preprint arXiv:2306.04901

2023/6/8

Peizhong Ju
Peizhong Ju

H-Index: 4

Sen Lin
Sen Lin

H-Index: 3

Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning

arXiv preprint arXiv:2306.00324

2023/6/1

Peizhong Ju
Peizhong Ju

H-Index: 4

Arnob Ghosh
Arnob Ghosh

H-Index: 11

On the generalization power of the overfitted three-layer neural tangent kernel model

Advances in Neural Information Processing Systems

2022/12/6

Peizhong Ju
Peizhong Ju

H-Index: 4

Xiaojun Lin
Xiaojun Lin

H-Index: 22

Understanding the Generalization Power of Overfitted NTK Models: 3-layer vs. 2-layer

2022/9/27

Peizhong Ju
Peizhong Ju

H-Index: 4

Xiaojun Lin
Xiaojun Lin

H-Index: 22

Distribution-level markets under high renewable energy penetration

2022/6/28

Peizhong Ju
Peizhong Ju

H-Index: 4

Xiaojun Lin
Xiaojun Lin

H-Index: 22

Robustness of Learning and Control

2021/11/10

Peizhong Ju
Peizhong Ju

H-Index: 4

On the generalization power of overfitted two-layer neural tangent kernel models

2021/7/1

Peizhong Ju
Peizhong Ju

H-Index: 4

Xiaojun Lin
Xiaojun Lin

H-Index: 22

Overfitting can be harmless for basis pursuit, but only to a degree

Advances in Neural Information Processing Systems

2020

See List of Professors in Peizhong Ju University(Purdue University)

Co-Authors

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