← Authors

Ruida Zhou

17 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (27) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ƒοΈ Keyword Collector (52) πŸ’Ž Century Club (17) πŸ”₯ Unstoppable (5) ⚑ Prolific Year (5)

Conferences

NIPS (6) AISTATS (5) ICLR (3) ICML (2) IJCAI (1)

Top co-authors

Chao Tian (8) Cong Shen (7) Tao Liu (5) P. R. Kumar (5) Jing Yang (4) Dileep Kalathil (3) Min Cheng (2) Chao Gan (1) Xi Liu (1) Li Fan (1)

Keywords

regret bound (5) natural policy gradient (3) multi-armed bandit (3) nash equilibrium (2) markov potential game (2) online learning (2) multi-agent system (2) upper confidence bound (2) sample complexity (2) function approximation (1) markov decision process (1) robust reinforcement learning (1) natural gradient (1) reinforcement learning (1) policy learning (1) bayesian optimization (1) policy evaluation (1) primal-dual algorithm (1) transformation invariance (1) sequential decision (1)

Papers

On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures ICML 2025
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning ICLR 2025
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery ICLR 2025
Cost-Aware Optimal Pairwise Pure Exploration AISTATS 2025
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning AISTATS 2025
Path-Guided Particle-based Sampling ICML 2024
Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024
Latent 3D Graph Diffusion ICLR 2024
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games NIPS 2023
Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation NIPS 2023
Federated Linear Bandits with Finite Adversarial Actions NIPS 2023
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning NIPS 2022
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales NIPS 2022
Approximate Top-$m$ Arm Identification with Heterogeneous Reward Variances AISTATS 2022
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs NIPS 2021
Regional Multi-Armed Bandits AISTATS 2018
Cost-aware Cascading Bandits IJCAI 2018