Xiao Zhang

Affiliations:
  • University of Virginia, Department of Computer Science, Charlottesville, VA, USA


According to our database1, Xiao Zhang authored at least 16 papers between 2017 and 2024.

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

Timeline

2017
2018
2019
2020
2021
2022
2023
2024
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Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Do Parameters Reveal More than Loss for Membership Inference?
CoRR, 2024

2023
When Can Linear Learners be Robust to Indiscriminate Poisoning Attacks?
CoRR, 2023

What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Understanding Intrinsic Robustness Using Label Uncertainty.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Improved Estimation of Concentration Under ℓp-Norm Distance Metrics Using Half Spaces.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Cost-Sensitive Robustness against Adversarial Examples.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning One-hidden-layer ReLU Networks via Gradient Descent.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery.
Proceedings of the 35th International Conference on Machine Learning, 2018

Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Unified Framework for Nonconvex Low-Rank plus Sparse Matrix Recovery.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption.
CoRR, 2017

A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Unified Computational and Statistical Framework for Nonconvex Low-rank Matrix Estimation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017


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