Ruida Zhou - RankMe

93 papers A* 12A 5B 13Misc 1Journal 57Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Binary Preferences: A Principled Framework for Reward Modeling with Ordinal Feedback. CoRR Amirhossein Afsharrad, Ruida Zhou, Luca Viano, Sanjay Lall, Mohammad Ghavamzadeh
2026	J	`jnl`	DISPO: Enhancing Training Efficiency and Stability in Reinforcement Learning for Large Language Model Mathematical Reasoning. CoRR Batuhan K. Karaman, Aditya Rawal, Suhaila Shakiah, Mohammad Ghavamzadeh, Mingyi Hong, Arijit Biswas, Ruida Zhou
2026	J	`jnl`	Direct Preference Optimization with Rating Information: Practical Algorithms and Provable Gains. CoRR Luca Viano, Ruida Zhou, Yifan Sun, Mahdi Namazifar, Volkan Cevher, Shoham Sabach, Mohammad Ghavamzadeh
2026	J	`jnl`	HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents. CoRR Jiangweizhi Peng, Yuanxin Liu, Ruida Zhou, Charles Fleming, Zhaoran Wang, Alfredo García, Mingyi Hong
2025	A	`conf`	ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. AISTATS Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi
2025	A	`conf`	Cost-Aware Optimal Pairwise Pure Exploration. AISTATS Di Wu, Chengshuai Shi, Ruida Zhou, Cong Shen
2025	J	`jnl`	Cost-Aware Optimal Pairwise Pure Exploration. CoRR Di Wu, Chengshuai Shi, Ruida Zhou, Cong Shen
2025	A*	`conf`	Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. ICLR Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang
2025	J	`jnl`	Directional-Clamp PPO. CoRR Gilad Karpel, Ruida Zhou, Shoham Sabach, Mohammad Ghavamzadeh
2025	A*	`conf`	On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. ICLR Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang
2025	A*	`conf`	On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures. ICML Wei Shen, Ruida Zhou, Jing Yang, Cong Shen
2025	J	`jnl`	On the optimal regret of collaborative personalized linear bandits. CoRR Bruce Huang, Ruida Zhou, Lin F. Yang, Suhas N. Diggavi
2025	B	`conf`	Personalized Heterogeneous Mean Estimation Under User-Level LDP. ISIT Ruida Zhou, Antonious M. Girgis, Suhas N. Diggavi
2025	J	`jnl`	SPIRE: Conditional Personalization for Federated Diffusion Generative Models. CoRR Kaan Ozkara, Ruida Zhou, Suhas N. Diggavi
2025	—	`conf`	Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning. CPAL Jie Peng, Sukwon Yun, Kaixiong Zhou, Ruida Zhou, Thomas Hartvigsen, Yanyong Zhang, Zhangyang Wang, Tianlong Chen
2025	J	`jnl`	Weakly Private Information Retrieval From Heterogeneously Trusted Servers. IEEE Trans. Inf. Theory Wenyuan Zhao, Yu-Shin Huang, Ruida Zhou, Chao Tian
2024	J	`jnl`	Correlational Lagrangian Schrödinger Bridge: Learning Dynamics with Population-Level Regularization. CoRR Yuning You, Ruida Zhou, Yang Shen
2024	J	`jnl`	Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. CoRR Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang
2024	J	`jnl`	Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. IEEE J. Sel. Areas Inf. Theory Ruida Zhou, Chao Tian, Tie Liu
2024	J	`jnl`	From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization. CoRR Qiang Zhang, Ruida Zhou, Yang Shen, Tie Liu
2024	J	`jnl`	Harnessing the Power of Federated Learning in Federated Contextual Bandits. Trans. Mach. Learn. Res. Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen
2024	J	`jnl`	Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. CoRR Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi
2024	A*	`conf`	Latent 3D Graph Diffusion. ICLR Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen
2024	J	`jnl`	On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. CoRR Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang
2024	J	`jnl`	On the Training Convergence of Transformers for In-Context Classification. CoRR Wei Shen, Ruida Zhou, Jing Yang, Cong Shen
2024	A*	`conf`	Path-Guided Particle-based Sampling. ICML Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian
2024	J	`jnl`	Path-Guided Particle-based Sampling. CoRR Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian
2024	B	`conf`	Personalized Heterogeneous Gaussian Mean Estimation Under Communication Constraints. ISIT Ruida Zhou, Suhas N. Diggavi
2024	A	`conf`	Provable Policy Gradient Methods for Average-Reward Markov Potential Games. AISTATS Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian
2024	J	`jnl`	Provable Policy Gradient Methods for Average-Reward Markov Potential Games. CoRR Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian
2024	J	`jnl`	Reframing Data Value for Large Language Models Through the Lens of Plausability. CoRR Mohamad Rida Rammal, Ruida Zhou, Suhas N. Diggavi
2024	—	`conf`	Research on Characteristics of Hesitant Driving Behavior in Urban Expressway Diversion Areas. IoTAAI Xiang Li, Ruida Zhou, Lanfang Zhang, Jun Zou, Jun Li
2024	—	`conf`	Staggered Quantizers for Perfect Perceptual Quality: A Connection Between Quantizers with Common Randomness and Without. ISIT (Workshops) Ruida Zhou, Chao Tian
2024	J	`jnl`	Staggered Quantizers for Perfect Perceptual Quality: A Connection between Quantizers with Common Randomness and Without. CoRR Ruida Zhou, Chao Tian
2024	J	`jnl`	Transformers learn variable-order Markov chains in-context. CoRR Ruida Zhou, Chao Tian, Suhas N. Diggavi
2024	J	`jnl`	Understanding Uncertainty-based Active Learning Under Model Mismatch. CoRR Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian
2024	B	`conf`	Weakly Private Information Retrieval from Heterogeneously Trusted Servers. ISIT Yu-Shin Huang, Wenyuan Zhao, Ruida Zhou, Chao Tian
2024	J	`jnl`	Weakly Private Information Retrieval from Heterogeneously Trusted Servers. CoRR Wenyuan Zhao, Yu-Shin Huang, Ruida Zhou, Chao Tian
2024	—	`conf`	When Uncertainty-Based Active Learning May Fail? ICPR (1) Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian
2023	B	`conf`	Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. ISIT Ruida Zhou, Chao Tian, Tie Liu
2023	J	`jnl`	Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. CoRR Ruida Zhou, Chao Tian, Tie Liu
2023	A*	`conf`	Federated Linear Bandits with Finite Adversarial Actions. NeurIPS Li Fan, Ruida Zhou, Chao Tian, Cong Shen
2023	J	`jnl`	Federated Linear Bandits with Finite Adversarial Actions. CoRR Li Fan, Ruida Zhou, Chao Tian, Cong Shen
2023	J	`jnl`	Harnessing the Power of Federated Learning in Federated Contextual Bandits. CoRR Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen
2023	A*	`conf`	Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation. NeurIPS Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian
2023	J	`jnl`	Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation. CoRR Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian
2023	A*	`conf`	Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games. NeurIPS Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour
2023	J	`jnl`	Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games. CoRR Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour
2023	J	`jnl`	Stochastic chaining and strengthened information-theoretic generalization bounds. J. Frankl. Inst. Ruida Zhou, Chao Tian, Tie Liu
2022	A*	`conf`	Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning. NeurIPS Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian
2022	J	`jnl`	Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning. CoRR Ruida Zhou, Tao Liu, Dileep M. Kalathil, P. R. Kumar, Chao Tian
2022	A	`conf`	Approximate Top-m Arm Identification with Heterogeneous Reward Variances. AISTATS Ruida Zhou, Chao Tian
2022	J	`jnl`	Approximate Top-m Arm Identification with Heterogeneous Reward Variances. CoRR Ruida Zhou, Chao Tian
2022	B	`conf`	Improved Weakly Private Information Retrieval Codes. ISIT Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu
2022	J	`jnl`	Improved Weakly Private Information Retrieval Codes. CoRR Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu
2022	J	`jnl`	Individually Conditional Individual Mutual Information Bound on Generalization Error. IEEE Trans. Inf. Theory Ruida Zhou, Chao Tian, Tie Liu
2022	A*	`conf`	Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales. NeurIPS Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu
2022	J	`jnl`	On Top-k Selection From m-Wise Partial Rankings via Borda Counting. IEEE Trans. Signal Process. Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen
2022	J	`jnl`	On Top-k Selection from m-wise Partial Rankings via Borda Counting. CoRR Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen
2022	B	`conf`	Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds. ISIT Ruida Zhou, Chao Tian, Tie Liu
2022	J	`jnl`	Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds. CoRR Ruida Zhou, Chao Tian, Tie Liu
2022	J	`jnl`	Two-Level Private Information Retrieval. IEEE J. Sel. Areas Inf. Theory Ruida Zhou, Chao Tian, Hua Sun, James S. Plank
2021	J	`jnl`	Computational Techniques for Investigating Information Theoretic Limits of Information Systems. Inf. Chao Tian, James S. Plank, Brent Hurst, Ruida Zhou
2021	J	`jnl`	Fast Global Convergence of Policy Optimization for Constrained MDPs. CoRR Tao Liu, Ruida Zhou, Dileep Kalathil, P. R. Kumar, Chao Tian
2021	B	`conf`	Individually Conditional Individual Mutual Information Bound on Generalization Error. ISIT Ruida Zhou, Chao Tian, Tie Liu
2021	A*	`conf`	Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs. NeurIPS Tao Liu, Ruida Zhou, Dileep Kalathil, Panganamala R. Kumar, Chao Tian
2021	J	`jnl`	Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs. CoRR Tao Liu, Ruida Zhou, Dileep Kalathil, P. R. Kumar, Chao Tian
2021	J	`jnl`	New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems. IEEE J. Sel. Areas Inf. Theory Tao Guo, Ruida Zhou, Chao Tian
2021	B	`conf`	Two-Level Private Information Retrieval. ISIT Ruida Zhou, Chao Tian, Hua Sun, James S. Plank
2021	J	`jnl`	Two-Level Private Information Retrieval. CoRR Ruida Zhou, Chao Tian, Hua Sun, James S. Plank
2020	J	`jnl`	Capacity-Achieving Private Information Retrieval Codes From MDS-Coded Databases With Minimum Message Size. IEEE Trans. Inf. Theory Ruida Zhou, Chao Tian, Hua Sun, Tie Liu
2020	J	`jnl`	Cost-Aware Cascading Bandits. IEEE Trans. Signal Process. Chao Gan, Ruida Zhou, Jing Yang, Cong Shen
2020	Misc	`conf`	Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. ITA Chao Gan, Ruida Zhou, Jing Yang, Cong Shen
2020	J	`jnl`	Individually Conditional Individual Mutual Information Bound on Generalization Error. CoRR Ruida Zhou, Chao Tian, Tie Liu
2020	J	`jnl`	Neighbor Cell List Optimization in Handover Management Using Cascading Bandits Algorithm. IEEE Access Chao Wang, Jian Yang, Huasen He, Ruida Zhou, Shuangwu Chen, Xiaofeng Jiang
2020	J	`jnl`	New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems. CoRR Tao Guo, Ruida Zhou, Chao Tian
2020	B	`conf`	On Top-k Selection from m-wise Partial Rankings via Borda Counting. ISIT Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen
2020	B	`conf`	On the Information Leakage in Private Information Retrieval Systems. ISIT Tao Guo, Ruida Zhou, Chao Tian
2020	J	`jnl`	On the Information Leakage in Private Information Retrieval Systems. IEEE Trans. Inf. Forensics Secur. Tao Guo, Ruida Zhou, Chao Tian
2020	B	`conf`	Weakly Private Information Retrieval Under the Maximal Leakage Metric. ISIT Ruida Zhou, Tao Guo, Chao Tian
2019	—	`conf`	A Cascading Bandit Approach To Efficient Mobility Management In Ultra-Dense Networks. MLSP Chao Wang, Ruida Zhou, Jing Yang, Cong Shen
2019	B	`conf`	Capacity-Achieving Private Information Retrieval Codes from MDS-Coded Databases with Minimum Message Size. ISIT Ruida Zhou, Chao Tian, Tie Liu, Hua Sun
2019	J	`jnl`	Capacity-Achieving Private Information Retrieval Codes from MDS-Coded Databases with Minimum Message Size. CoRR Ruida Zhou, Chao Tian, Hua Sun, Tie Liu
2019	J	`jnl`	Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. IEEE Trans. Cogn. Commun. Netw. Chao Gan, Ruida Zhou, Jing Yang, Cong Shen
2019	J	`jnl`	On the Information Leakage in Private Information Retrieval Systems. CoRR Tao Guo, Ruida Zhou, Chao Tian
2019	B	`conf`	Online Learning with Diverse User Preferences. ISIT Chao Gan, Jing Yang, Ruida Zhou, Cong Shen
2018	J	`jnl`	Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. CoRR Chao Gan, Ruida Zhou, Jing Yang, Cong Shen
2018	A*	`conf`	Cost-aware Cascading Bandits. IJCAI Ruida Zhou, Chao Gan, Jing Yang, Cong Shen
2018	J	`jnl`	Cost-aware Cascading Bandits. CoRR Ruida Zhou, Chao Gan, Jing Yang, Cong Shen
2018	J	`jnl`	Generalized Global Bandit and Its Application in Cellular Coverage Optimization. IEEE J. Sel. Top. Signal Process. Cong Shen, Ruida Zhou, Cem Tekin, Mihaela van der Schaar
2018	J	`jnl`	Regional Multi-Armed Bandits With Partial Informativeness. IEEE Trans. Signal Process. Zhiyang Wang, Ruida Zhou, Cong Shen
2018	A	`conf`	Regional Multi-Armed Bandits. AISTATS Zhiyang Wang, Ruida Zhou, Cong Shen
2018	J	`jnl`	Regional Multi-Armed Bandits. CoRR Zhiyang Wang, Ruida Zhou, Cong Shen