Ganghua Wang

According to our database, Ganghua Wang authored at least 12 papers between 2017 and 2024.

Collaborative distances:

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

2024

On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains.

Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding

CoRR, 2024

Drift to Remember.

Jin Du, Xinhe Zhang, Hao Shen, Xun Xian, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Na Li, Jia Liu, Jie Ding

CoRR, 2024

RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees.

Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding

CoRR, 2024

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective.

Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization.

Gen Li, Ganghua Wang, Jie Ding

IEEE Trans. Inf. Theory, September, 2023

Mitigating Group Bias in Federated Learning: Beyond Local Fairness.

Ganghua Wang, Ali Payani, Myungjin Lee, Ramana Kompella

CoRR, 2023

A Unified Detection Framework for Inference-Stage Backdoor Defenses.

Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Backdoor Attacks through the Adaptability Hypothesis.

Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the International Conference on Machine Learning, 2023

Pruning Deep Neural Networks from a Sparsity Perspective.

Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation.

Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang

CoRR, 2022

2021

Subset Privacy: Draw from an Obfuscated Urn.

Ganghua Wang, Jie Ding

CoRR, 2021

2017

Error estimates on a finite volume method for diffusion problems with interface on rectangular grids.

Jie Peng, Shi Shu, Haiyuan Yu, Chunsheng Feng, Mingxian Kan, Ganghua Wang

Appl. Math. Comput., 2017