47 citations · 96 across the 10 of their papers we have counts for
11 papers
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin A. Inan, Arturs Backurs +3
Positioned between pre-training and user deployment, aligning large language models (LLMs) through reinforcement learning (RL) has emerged as a prevailing strategy for training ins…
SoK: Privacy-Preserving Data Synthesis
Yuzheng Hu, Fan Wu, Qinbin Li +7
As the prevalence of data analysis grows, safeguarding data privacy has become a paramount concern. Consequently, there has been an upsurge in the development of mechanisms aimed a…
Factor Graph Neural Networks
Zhen Zhang, Mohammed Haroon Dupty, Fan Wu +2
In recent years, we have witnessed a surge of Graph Neural Networks (GNNs), most of which can learn powerful representations in an end-to-end fashion with great success in many rea…
Understanding the Impact of Adversarial Robustness on Accuracy Disparity
Yuzheng Hu, Fan Wu, Hongyang Zhang +1
While it has long been empirically observed that adversarial robustness may be at odds with standard accuracy and may have further disparate impacts on different classes, it remain…
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination
Zhuowen Yuan, Fan Wu, Yunhui Long +2
Transfer learning through the use of pre-trained models has become a growing trend for the machine learning community. Consequently, numerous pre-trained models are released online…
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks
Fan Wu, Linyi Li, Chejian Xu +5
As reinforcement learning (RL) has achieved near human-level performance in a variety of tasks, its robustness has raised great attention. While a vast body of research has explore…
LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis
Fan Wu, Yunhui Long, Ce Zhang +1
Graph structured data have enabled several successful applications such as recommendation systems and traffic prediction, given the rich node features and edges information. Howeve…
CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing
Fan Wu, Linyi Li, Zijian Huang +3
As reinforcement learning (RL) has achieved great success and been even adopted in safety-critical domains such as autonomous vehicles, a range of empirical studies have been condu…
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
Boxin Wang, Fan Wu, Yunhui Long +3
Recent success of deep neural networks (DNNs) hinges on the availability of large-scale dataset; however, training on such dataset often poses privacy risks for sensitive training…
The Twelvefold Way of Non-Sequential Lossless Compression
Taha Ameen ur Rahman, Alton S. Barbehenn, Xinan Chen +27
Many information sources are not just sequences of distinguishable symbols but rather have invariances governed by alternative counting paradigms such as permutations, combinations…
Factor Graph Neural Network
Zhen Zhang, Fan Wu, Wee Sun Lee
Most of the successful deep neural network architectures are structured, often consisting of elements like convolutional neural networks and gated recurrent neural networks. Recent…