Guang Cheng

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 25

Top Topics

Algorithmic Stability

Nearest Neighbor Algorithm

Top Venues

Trans. Mach. Learn. Res.

Publications

Lan Tao, Shirong Xu, Chi-Hua Wang, Namjoon Suh, Guang Cheng
Discriminative Estimation of Total Variation Distance: A Fidelity Auditor for Generative Data. CoRR (2024)
Din-Yin Hsieh, Chi-Hua Wang, Guang Cheng
Improve Fidelity and Utility of Synthetic Credit Card Transaction Time Series from Data-centric Perspective. CoRR (2024)
Tian-Yi Zhou, Namjoon Suh, Guang Cheng, Xiaoming Huo
Approximation of RKHS Functionals by Neural Networks. CoRR (2024)
Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS (2024)
Yinan Cheng, Chi-Hua Wang, Vamsi K. Potluru, Tucker Balch, Guang Cheng
Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models. CoRR (2024)
Joshua John Ward, Xianli Zeng, Guang Cheng
FairRR: Pre-Processing for Group Fairness through Randomized Response. AISTATS (2024)
Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng
Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR (2024)
Chi-Hua Wang, Guang Cheng
BadGD: A unified data-centric framework to identify gradient descent vulnerabilities. CoRR (2024)
Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR (2024)
Xianli Zeng, Joshua Ward, Guang Cheng
FairRR: Pre-Processing for Group Fairness through Randomized Response. CoRR (2024)
Joshua Ward, Chi-Hua Wang, Guang Cheng
Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Models. CoRR (2024)
Shirong Xu, Will Wei Sun, Guang Cheng
Rate-Optimal Rank Aggregation with Private Pairwise Rankings. CoRR (2024)
Shirong Xu, Chendi Wang, Will Wei Sun, Guang Cheng
Binary Classification under Local Label Differential Privacy Using Randomized Response Mechanisms. Trans. Mach. Learn. Res. 2023 (2023)
Shirong Xu, Will Wei Sun, Guang Cheng
Utility Theory of Synthetic Data Generation. CoRR (2023)
Yuantong Li, Guang Cheng, Xiaowu Dai
Double Matching Under Complementary Preferences. CoRR (2023)
Wenjie Li, Chi-Hua Wang, Guang Cheng, Qifan Song
Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization. Trans. Mach. Learn. Res. 2023 (2023)
Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng
Variance reduction on general adaptive stochastic mirror descent. Mach. Learn. 111 (12) (2022)
Yue Xing, Qifan Song, Guang Cheng
Phase Transition from Clean Training to Adversarial Training. NeurIPS (2022)
Yue Xing, Qifan Song, Guang Cheng
Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. 4 (2) (2022)
Yue Xing, Qifan Song, Guang Cheng
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS (2022)
Yucong Liu, Chi-Hua Wang, Guang Cheng
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation. CoRR (2022)
Zhanyu Wang, Guang Cheng, Jordan Awan
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies. CoRR (2022)
Yang Yu, Shih-Kang Chao, Guang Cheng
Distributed Bootstrap for Simultaneous Inference Under High Dimensionality. J. Mach. Learn. Res. 23 (2022)
Yue Xing, Qifan Song, Guang Cheng
Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS (2022)
Yue Xing, Qifan Song, Guang Cheng
On the Algorithmic Stability of Adversarial Training. NeurIPS (2021)