← Authors

Yuejie Chi

56 papers · 2013–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (19) 🐝 Cross-Pollinator (4) 🀝 Dynamic Duo (18) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”¬ Deep Specialist (17) 🧬 Topic Evolution πŸ”₯ Unstoppable (10) πŸš€ Conference Pioneer ⚑ Prolific Year (13) πŸ’Ž Century Club (56) πŸ—ƒοΈ Keyword Collector (56)

Conferences

NIPS (18) ICML (14) ICLR (7) JMLR (7) AISTATS (6) AAAI (1) COLT (1) CVPR (1) UAI (1)

Top co-authors

Yuxin Chen (18) Yuting Wei (13) Gen Li (12) Laixi Shi (10) Shicong Cen (9) Cong Ma (6) Yuantao Gu (6) Tong Yang (5) Lingjing Kong (4) Yingbin Liang (4)

Research topics

Differential Privacy (1)

Keywords

sample complexity (12) gradient descent (6) nonconvex optimization (6) federated learning (6) variance reduction (5) markov decision process (5) offline reinforcement learning (4) reinforcement learning (4) generative model (4) multi-agent reinforcement learning (3) matrix completion (3) spectral initialization (3) scaled gradient descent (3) nash equilibrium (3) markov game (3) phase retrieval (3) distributed optimization (3) communication compression (3) gradient tracking (3) federated q-learning (3)

Papers

Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization AISTATS 2025
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning ICML 2025
ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference ICML 2025
Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning ICLR 2025
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF ICLR 2025
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond JMLR 2025
Vertical Federated Learning with Missing Features During Training and Inference ICLR 2025
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers ICLR 2025
Faster WIND: Accelerating Iterative Best-of-$N$ Distillation for LLM Alignment AISTATS 2025
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games ICML 2025
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning NIPS 2024
Accelerating Convergence of Score-Based Diffusion Models, Provably ICML 2024
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference ICML 2024
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NIPS 2024
Learning Discrete Concepts in Latent Hierarchical Models NIPS 2024
The Sample-Communication Complexity Trade-off in Federated Q-Learning NIPS 2024
In-Context Learning with Representations: Contextual Generalization of Trained Transformers NIPS 2024
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty ICML 2024
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization JMLR 2024
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression AISTATS 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices ICML 2024
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models ICLR 2024
Counterfactual Generation with Identifiability Guarantees NIPS 2023
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning NIPS 2023
A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning UAI 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable Models CVPR 2023
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games ICLR 2023
Asynchronous Gradient Play in Zero-Sum Multi-agent Games ICLR 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing ICML 2023
Identification of Nonlinear Latent Hierarchical Models NIPS 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model NIPS 2023
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation NIPS 2023
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond ICML 2023
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion AISTATS 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression NIPS 2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model NIPS 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression NIPS 2022
Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning AAAI 2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity ICML 2022
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements JMLR 2022
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization NIPS 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning NIPS 2021
Softmax Policy Gradient Methods Can Take Exponential Time to Converge COLT 2021
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent JMLR 2021
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning ICML 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting NIPS 2021
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model NIPS 2020
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction NIPS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction AISTATS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion ICML 2018
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms JMLR 2017
Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow ICML 2016
Spectral Compressed Sensing via Structured Matrix Completion ICML 2013