most citedAutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizing

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML20235 cited

AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizing

Namjoon Suh, Xiaofeng Lin, Din-Yin Hsieh +2

Diffusion model has become a main paradigm for synthetic data generation in many subfields of modern machine learning, including computer vision, language model, or speech synthesi…

eess.SY2023

Leveraging Untrustworthy Commands for Multi-Robot Coordination in Unpredictable Environments: A Bandit Submodular Maximization Approach

Zirui Xu, Xiaofeng Lin, Vasileios Tzoumas

We study the problem of multi-agent coordination in unpredictable and partially-observable environments with untrustworthy external commands. The commands are actions suggested to…

cs.LG2023

Estimating Treatment Effects Under Heterogeneous Interference

Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu +3

Treatment effect estimation can assist in effective decision-making in e-commerce, medicine, and education. One popular application of this estimation lies in the prediction of the…

eess.SY2023

Bandit Submodular Maximization for Multi-Robot Coordination in Unpredictable and Partially Observable Environments

Zirui Xu, Xiaofeng Lin, Vasileios Tzoumas

We study the problem of multi-agent coordination in unpredictable and partially observable environments, that is, environments whose future evolution is unknown a priori and that c…

cs.CV20224 cited

FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification

Xiaofeng Lin, Seungbae Kim, Jungseock Joo

Existing pruning techniques preserve deep neural networks' overall ability to make correct predictions but may also amplify hidden biases during the compression process. We propose…