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Ruida Zhou
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2020 – today
- 2024
- [j15]Ruida Zhou, Chao Tian, Tie Liu:
Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. IEEE J. Sel. Areas Inf. Theory 5: 94-104 (2024) - [j14]Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen:
Harnessing the Power of Federated Learning in Federated Contextual Bandits. Trans. Mach. Learn. Res. 2024 (2024) - [c28]Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian:
Provable Policy Gradient Methods for Average-Reward Markov Potential Games. AISTATS 2024: 4699-4707 - [c27]Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen:
Latent 3D Graph Diffusion. ICLR 2024 - [c26]Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian:
Path-Guided Particle-based Sampling. ICML 2024 - [c25]Xiang Li, Ruida Zhou, Lanfang Zhang, Jun Zou, Jun Li:
Research on Characteristics of Hesitant Driving Behavior in Urban Expressway Diversion Areas. IoTAAI 2024: 168-175 - [c24]Ruida Zhou, Chao Tian:
Staggered Quantizers for Perfect Perceptual Quality: A Connection Between Quantizers with Common Randomness and Without. ISIT (Workshops) 2024: 1-6 - [c23]Ruida Zhou, Suhas N. Diggavi:
Personalized Heterogeneous Gaussian Mean Estimation Under Communication Constraints. ISIT 2024: 981-986 - [c22]Yu-Shin Huang, Wenyuan Zhao, Ruida Zhou, Chao Tian:
Weakly Private Information Retrieval from Heterogeneously Trusted Servers. ISIT 2024: 2862-2867 - [i32]Qiang Zhang, Ruida Zhou, Yang Shen, Tie Liu:
From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization. CoRR abs/2401.02019 (2024) - [i31]Yuning You, Ruida Zhou, Yang Shen:
Correlational Lagrangian Schrödinger Bridge: Learning Dynamics with Population-Level Regularization. CoRR abs/2402.10227 (2024) - [i30]Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi:
Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. CoRR abs/2402.12537 (2024) - [i29]Wenyuan Zhao, Yu-Shin Huang, Ruida Zhou, Chao Tian:
Weakly Private Information Retrieval from Heterogeneously Trusted Servers. CoRR abs/2402.17940 (2024) - [i28]Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian:
Provable Policy Gradient Methods for Average-Reward Markov Potential Games. CoRR abs/2403.05738 (2024) - [i27]Ruida Zhou, Chao Tian:
Staggered Quantizers for Perfect Perceptual Quality: A Connection between Quantizers with Common Randomness and Without. CoRR abs/2406.19248 (2024) - [i26]Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian:
Understanding Uncertainty-based Active Learning Under Model Mismatch. CoRR abs/2408.13690 (2024) - [i25]Mohamad Rida Rammal, Ruida Zhou, Suhas N. Diggavi:
Reframing Data Value for Large Language Models Through the Lens of Plausability. CoRR abs/2409.00284 (2024) - [i24]Ruida Zhou, Chao Tian, Suhas N. Diggavi:
Transformers learn variable-order Markov chains in-context. CoRR abs/2410.05493 (2024) - [i23]Wei Shen, Ruida Zhou, Jing Yang, Cong Shen:
On the Training Convergence of Transformers for In-Context Classification. CoRR abs/2410.11778 (2024) - [i22]Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang:
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. CoRR abs/2410.12085 (2024) - [i21]Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang:
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. CoRR abs/2410.13981 (2024) - 2023
- [j13]Ruida Zhou, Chao Tian, Tie Liu:
Stochastic chaining and strengthened information-theoretic generalization bounds. J. Frankl. Inst. 360(6): 4114-4134 (2023) - [c21]Ruida Zhou, Chao Tian, Tie Liu:
Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. ISIT 2023: 903-908 - [c20]Li Fan, Ruida Zhou, Chao Tian, Cong Shen:
Federated Linear Bandits with Finite Adversarial Actions. NeurIPS 2023 - [c19]Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour:
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games. NeurIPS 2023 - [c18]Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian:
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation. NeurIPS 2023 - [i20]Ruida Zhou, Chao Tian, Tie Liu:
Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. CoRR abs/2305.00876 (2023) - [i19]Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian:
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation. CoRR abs/2307.08875 (2023) - [i18]Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour:
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games. CoRR abs/2310.09727 (2023) - [i17]Li Fan, Ruida Zhou, Chao Tian, Cong Shen:
Federated Linear Bandits with Finite Adversarial Actions. CoRR abs/2311.00973 (2023) - [i16]Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen:
Harnessing the Power of Federated Learning in Federated Contextual Bandits. CoRR abs/2312.16341 (2023) - 2022
- [j12]Ruida Zhou, Chao Tian, Hua Sun, James S. Plank:
Two-Level Private Information Retrieval. IEEE J. Sel. Areas Inf. Theory 3(2): 337-349 (2022) - [j11]Ruida Zhou, Chao Tian, Tie Liu:
Individually Conditional Individual Mutual Information Bound on Generalization Error. IEEE Trans. Inf. Theory 68(5): 3304-3316 (2022) - [j10]Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen:
On Top-k Selection From m-Wise Partial Rankings via Borda Counting. IEEE Trans. Signal Process. 70: 2031-2045 (2022) - [c17]Ruida Zhou, Chao Tian:
Approximate Top-m Arm Identification with Heterogeneous Reward Variances. AISTATS 2022: 7483-7504 - [c16]Ruida Zhou, Chao Tian, Tie Liu:
Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds. ISIT 2022: 690-695 - [c15]Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu:
Improved Weakly Private Information Retrieval Codes. ISIT 2022: 2827-2832 - [c14]Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu:
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales. NeurIPS 2022 - [c13]Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian:
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning. NeurIPS 2022 - [i15]Ruida Zhou, Chao Tian, Tie Liu:
Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds. CoRR abs/2201.12192 (2022) - [i14]Ruida Zhou, Chao Tian:
Approximate Top-m Arm Identification with Heterogeneous Reward Variances. CoRR abs/2204.05245 (2022) - [i13]Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen:
On Top-k Selection from m-wise Partial Rankings via Borda Counting. CoRR abs/2204.05742 (2022) - [i12]Chengyuan Qian, Ruida Zhou, Chao Tian, Tie Liu:
Improved Weakly Private Information Retrieval Codes. CoRR abs/2205.01611 (2022) - [i11]Ruida Zhou, Tao Liu, Dileep M. Kalathil, P. R. Kumar, Chao Tian:
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning. CoRR abs/2206.05357 (2022) - 2021
- [j9]Chao Tian, James S. Plank, Brent Hurst, Ruida Zhou:
Computational Techniques for Investigating Information Theoretic Limits of Information Systems. Inf. 12(2): 82 (2021) - [j8]Tao Guo, Ruida Zhou, Chao Tian:
New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems. IEEE J. Sel. Areas Inf. Theory 2(1): 403-414 (2021) - [c12]Ruida Zhou, Chao Tian, Tie Liu:
Individually Conditional Individual Mutual Information Bound on Generalization Error. ISIT 2021: 670-675 - [c11]Ruida Zhou, Chao Tian, Hua Sun, James S. Plank:
Two-Level Private Information Retrieval. ISIT 2021: 1919-1924 - [c10]Tao Liu, Ruida Zhou, Dileep Kalathil, Panganamala R. Kumar, Chao Tian:
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs. NeurIPS 2021: 17183-17193 - [i10]Ruida Zhou, Chao Tian, Hua Sun, James S. Plank:
Two-Level Private Information Retrieval. CoRR abs/2101.04821 (2021) - [i9]Tao Liu, Ruida Zhou, Dileep Kalathil, P. R. Kumar, Chao Tian:
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs. CoRR abs/2106.02684 (2021) - [i8]Tao Liu, Ruida Zhou, Dileep Kalathil, P. R. Kumar, Chao Tian:
Fast Global Convergence of Policy Optimization for Constrained MDPs. CoRR abs/2111.00552 (2021) - 2020
- [j7]Chao Wang, Jian Yang, Huasen He, Ruida Zhou, Shuangwu Chen, Xiaofeng Jiang:
Neighbor Cell List Optimization in Handover Management Using Cascading Bandits Algorithm. IEEE Access 8: 134137-134150 (2020) - [j6]Tao Guo, Ruida Zhou, Chao Tian:
On the Information Leakage in Private Information Retrieval Systems. IEEE Trans. Inf. Forensics Secur. 15: 2999-3012 (2020) - [j5]Ruida Zhou, Chao Tian, Hua Sun, Tie Liu:
Capacity-Achieving Private Information Retrieval Codes From MDS-Coded Databases With Minimum Message Size. IEEE Trans. Inf. Theory 66(8): 4904-4916 (2020) - [j4]Chao Gan, Ruida Zhou, Jing Yang, Cong Shen:
Cost-Aware Cascading Bandits. IEEE Trans. Signal Process. 68: 3692-3706 (2020) - [c9]Tao Guo, Ruida Zhou, Chao Tian:
On the Information Leakage in Private Information Retrieval Systems. ISIT 2020: 1018-1023 - [c8]Ruida Zhou, Tao Guo, Chao Tian:
Weakly Private Information Retrieval Under the Maximal Leakage Metric. ISIT 2020: 1089-1094 - [c7]Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen:
On Top-k Selection from m-wise Partial Rankings via Borda Counting. ISIT 2020: 2759-2764 - [c6]Chao Gan, Ruida Zhou, Jing Yang, Cong Shen:
Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. ITA 2020: 1-12 - [i7]Tao Guo, Ruida Zhou, Chao Tian:
New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems. CoRR abs/2008.00960 (2020) - [i6]Ruida Zhou, Chao Tian, Tie Liu:
Individually Conditional Individual Mutual Information Bound on Generalization Error. CoRR abs/2012.09922 (2020)
2010 – 2019
- 2019
- [j3]Chao Gan, Ruida Zhou, Jing Yang, Cong Shen:
Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. IEEE Trans. Cogn. Commun. Netw. 5(1): 15-27 (2019) - [c5]Ruida Zhou, Chao Tian, Tie Liu, Hua Sun:
Capacity-Achieving Private Information Retrieval Codes from MDS-Coded Databases with Minimum Message Size. ISIT 2019: 370-374 - [c4]Chao Gan, Jing Yang, Ruida Zhou, Cong Shen:
Online Learning with Diverse User Preferences. ISIT 2019: 2539-2543 - [c3]Chao Wang, Ruida Zhou, Jing Yang, Cong Shen:
A Cascading Bandit Approach To Efficient Mobility Management In Ultra-Dense Networks. MLSP 2019: 1-6 - [i5]Ruida Zhou, Chao Tian, Hua Sun, Tie Liu:
Capacity-Achieving Private Information Retrieval Codes from MDS-Coded Databases with Minimum Message Size. CoRR abs/1903.08229 (2019) - [i4]Tao Guo, Ruida Zhou, Chao Tian:
On the Information Leakage in Private Information Retrieval Systems. CoRR abs/1909.11605 (2019) - 2018
- [j2]Cong Shen, Ruida Zhou, Cem Tekin, Mihaela van der Schaar:
Generalized Global Bandit and Its Application in Cellular Coverage Optimization. IEEE J. Sel. Top. Signal Process. 12(1): 218-232 (2018) - [j1]Zhiyang Wang, Ruida Zhou, Cong Shen:
Regional Multi-Armed Bandits With Partial Informativeness. IEEE Trans. Signal Process. 66(21): 5705-5717 (2018) - [c2]Zhiyang Wang, Ruida Zhou, Cong Shen:
Regional Multi-Armed Bandits. AISTATS 2018: 510-518 - [c1]Ruida Zhou, Chao Gan, Jing Yang, Cong Shen:
Cost-aware Cascading Bandits. IJCAI 2018: 3228-3234 - [i3]Zhiyang Wang, Ruida Zhou, Cong Shen:
Regional Multi-Armed Bandits. CoRR abs/1802.07917 (2018) - [i2]Chao Gan, Ruida Zhou, Jing Yang, Cong Shen:
Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. CoRR abs/1804.04048 (2018) - [i1]Ruida Zhou, Chao Gan, Jing Yang, Cong Shen:
Cost-aware Cascading Bandits. CoRR abs/1805.08638 (2018)
Coauthor Index
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last updated on 2024-11-26 21:39 CET by the dblp team
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