Jiawei Zhang

Orcid: 0000-0002-8091-5045

Affiliations:
  • Chinese University of Hong Kong, School of Science and Engineering, Shenzhen, China
  • Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, MA, USA


According to our database1, Jiawei Zhang authored at least 25 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2019
2020
2021
2022
2023
2024
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Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Drift to Remember.
CoRR, 2024

Additive-Effect Assisted Learning.
CoRR, 2024

Uniformly Stable Algorithms for Adversarial Training and Beyond.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Smoothed Bregman Proximal Gradient Algorithm for Decentralized Nonconvex Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Assisted Unsupervised Domain Adaptation.
Proceedings of the IEEE International Symposium on Information Theory, 2023

Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation.
Proceedings of the International Conference on Machine Learning, 2023

Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach.
Proceedings of the International Conference on Machine Learning, 2023

Pruning Deep Neural Networks from a Sparsity Perspective.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization.
SIAM J. Optim., September, 2022

Decentralized Non-Convex Learning With Linearly Coupled Constraints: Algorithm Designs and Application to Vertical Learning Problem.
IEEE Trans. Signal Process., 2022

Parallel Assisted Learning.
IEEE Trans. Signal Process., 2022

What is a Good Metric to Study Generalization of Minimax Learners?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Distributed Stochastic Consensus Optimization With Momentum for Nonconvex Nonsmooth Problems.
IEEE Trans. Signal Process., 2021

Targeted Cross-Validation.
CoRR, 2021

Decentralized Non-Convex Learning with Linearly Coupled Constraints.
CoRR, 2021

When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
A Proximal Alternating Direction Method of Multiplier for Linearly Constrained Nonconvex Minimization.
SIAM J. Optim., 2020

A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Exact O(N<sup>2</sup>) Hyper-Parameter Optimization for Gaussian Process Regression.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

A Proximal Dual Consensus Method for Linearly Coupled Multi-Agent Non-Convex Optimization.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Binary Regression Adaptive Goodness-of-fit Test (BAGofT).
CoRR, 2019

A General O(n<sup>2</sup>) Hyper-Parameter Optimization for Gaussian Process Regression with Cross-Validation and Non-linearly Constrained ADMM.
CoRR, 2019

Scalable Gaussian Process Using Inexact Admm for Big Data.
Proceedings of the IEEE International Conference on Acoustics, 2019


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