| 2025 | AISTATS | ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. | Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi |
| 2025 | AISTATS | Cost-Aware Optimal Pairwise Pure Exploration. | Di Wu, Chengshuai Shi, Ruida Zhou, Cong Shen |
| 2025 | ICLR | Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. | Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang |
| 2025 | ICLR | On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. | Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang |
| 2025 | ICML | On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures. | Wei Shen, Ruida Zhou, Jing Yang, Cong Shen |
| 2025 | ISIT | Personalized Heterogeneous Mean Estimation Under User-Level LDP. | Ruida Zhou, Antonious M. Girgis, Suhas N. Diggavi |
| 2024 | AISTATS | Provable Policy Gradient Methods for Average-Reward Markov Potential Games. | Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian |
| 2024 | ICLR | Latent 3D Graph Diffusion. | Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen |
| 2024 | ICML | Path-Guided Particle-based Sampling. | Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian |
| 2024 | ICPR | When Uncertainty-Based Active Learning May Fail? | Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian |
| 2024 | ISIT | Weakly Private Information Retrieval from Heterogeneously Trusted Servers. | Yu-Shin Huang, Wenyuan Zhao, Ruida Zhou, Chao Tian |
| 2024 | ISIT | Staggered Quantizers for Perfect Perceptual Quality: A Connection Between Quantizers with Common Randomness and Without. | Ruida Zhou, Chao Tian |
| 2024 | ISIT | Personalized Heterogeneous Gaussian Mean Estimation Under Communication Constraints. | Ruida Zhou, Suhas N. Diggavi |
| 2023 | ISIT | Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. | Ruida Zhou, Chao Tian, Tie Liu |
| 2022 | AISTATS | Approximate Top-m Arm Identification with Heterogeneous Reward Variances. | Ruida Zhou, Chao Tian |
| 2022 | ISIT | Improved Weakly Private Information Retrieval Codes. | Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu |
| 2022 | ISIT | Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds. | Ruida Zhou, Chao Tian, Tie Liu |
| 2021 | ISIT | Individually Conditional Individual Mutual Information Bound on Generalization Error. | Ruida Zhou, Chao Tian, Tie Liu |
| 2021 | ISIT | Two-Level Private Information Retrieval. | Ruida Zhou, Chao Tian, Hua Sun, James S. Plank |
| 2020 | ISIT | On Top-k Selection from m-wise Partial Rankings via Borda Counting. | Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen |
| 2020 | ISIT | On the Information Leakage in Private Information Retrieval Systems. | Tao Guo, Ruida Zhou, Chao Tian |
| 2020 | ISIT | Weakly Private Information Retrieval Under the Maximal Leakage Metric. | Ruida Zhou, Tao Guo, Chao Tian |
| 2020 | ITA | Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. | Chao Gan, Ruida Zhou, Jing Yang, Cong Shen |
| 2019 | ISIT | Online Learning with Diverse User Preferences. | Chao Gan, Jing Yang, Ruida Zhou, Cong Shen |
| 2019 | ISIT | Capacity-Achieving Private Information Retrieval Codes from MDS-Coded Databases with Minimum Message Size. | Ruida Zhou, Chao Tian, Tie Liu, Hua Sun |
| 2018 | AISTATS | Regional Multi-Armed Bandits. | Zhiyang Wang, Ruida Zhou, Cong Shen |
| 2018 | IJCAI | Cost-aware Cascading Bandits. | Ruida Zhou, Chao Gan, Jing Yang, Cong Shen |