Zhuoran Yang
Orcid: 0000-0001-5269-9958
According to our database1,
Zhuoran Yang
authored at least 191 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
IEEE Trans. Pattern Anal. Mach. Intell., February, 2024
Pessimistic value iteration for multi-task data sharing in Offline Reinforcement Learning.
Artif. Intell., January, 2024
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory.
CoRR, 2024
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games.
CoRR, 2024
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality.
CoRR, 2024
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning.
CoRR, 2024
CoRR, 2024
2023
Math. Oper. Res., August, 2023
Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust.
Proc. ACM Hum. Comput. Interact., April, 2023
A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic.
SIAM J. Optim., March, 2023
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium.
Math. Oper. Res., February, 2023
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?
J. Mach. Learn. Res., 2023
CoRR, 2023
CoRR, 2023
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation.
CoRR, 2023
Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks.
CoRR, 2023
CoRR, 2023
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization.
CoRR, 2023
CoRR, 2023
One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration.
CoRR, 2023
A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations.
CoRR, 2023
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning.
CoRR, 2023
Partial Discharge Characteristics and Growth Stage Recognition of Electrical Tree in XLPE Insulation.
IEEE Access, 2023
Proceedings of the 24th ACM Conference on Economics and Computation, 2023
Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning.
Proceedings of the Learning for Dynamics and Control Conference, 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP.
Proceedings of the International Conference on Machine Learning, 2023
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments.
Proceedings of the International Conference on Machine Learning, 2023
Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning.
Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems, 2023
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information.
CoRR, 2022
Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes.
CoRR, 2022
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments.
CoRR, 2022
Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency.
CoRR, 2022
Sample-Efficient Reinforcement Learning for POMDPs with Linear Function Approximations.
CoRR, 2022
The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches.
CoRR, 2022
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach.
CoRR, 2022
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning.
CoRR, 2022
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022
Accelerate online reinforcement learning for building HVAC control with heterogeneous expert guidances.
Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, 2022
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets.
Proceedings of the International Conference on Machine Learning, 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022
Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation.
Proceedings of the International Conference on Machine Learning, 2022
Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy.
Proceedings of the International Conference on Machine Learning, 2022
Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes.
Proceedings of the International Conference on Machine Learning, 2022
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency.
Proceedings of the International Conference on Machine Learning, 2022
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents.
IEEE Trans. Autom. Control., 2021
Decentralized multi-agent reinforcement learning with networked agents: recent advances.
Frontiers Inf. Technol. Electron. Eng., 2021
IEEE J. Sel. Areas Inf. Theory, 2021
Efficient and doubly-robust methods for variable selection and parameter estimation in longitudinal data analysis.
Comput. Stat., 2021
Commun. Stat. Simul. Comput., 2021
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers?
CoRR, 2021
ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning.
CoRR, 2021
CoRR, 2021
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima.
CoRR, 2021
Provably Efficient Generative Adversarial Imitation Learning for Online and Offline Setting with Linear Function Approximation.
CoRR, 2021
CoRR, 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation.
CoRR, 2021
CoRR, 2021
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization.
CoRR, 2021
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game.
Proceedings of the 38th International Conference on Machine Learning, 2021
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Randomized Exploration in Reinforcement Learning with General Value Function Approximation.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
A Novel Model Integrating Deep Learning for Land Use/Cover Change Reconstruction: A Case Study of Zhenlai County, Northeast China.
Remote. Sens., 2020
Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy.
CoRR, 2020
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization.
CoRR, 2020
Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations.
CoRR, 2020
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning.
CoRR, 2020
Understanding Implicit Regularization in Over-Parameterized Nonlinear Statistical Model.
CoRR, 2020
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic.
CoRR, 2020
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach.
CoRR, 2020
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate.
CoRR, 2020
Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate.
Proceedings of the 37th International Conference on Machine Learning, 2020
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis.
Proceedings of the 37th International Conference on Machine Learning, 2020
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
2019
Math. Program., 2019
J. Mach. Learn. Res., 2019
CoRR, 2019
CoRR, 2019
Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis.
CoRR, 2019
Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization.
CoRR, 2019
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost.
CoRR, 2019
CoRR, 2019
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning.
CoRR, 2019
Surface Charge Transport Characteristics of ZnO/Silicone Rubber Composites Under Impulse Superimposed on DC Voltage.
IEEE Access, 2019
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data.
Proceedings of the 36th International Conference on Machine Learning, 2019
Research Character Analyzation of Urban Security Based on Urban Resilience Using Big Data Method.
Proceedings of the Big Data and Security - First International Conference, 2019
Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition.
Proceedings of the IEEE Data Science Workshop, 2019
A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
Proceedings of the 18th IEEE/ACIS International Conference on Computer and Information Science, 2019
2018
CoRR, 2018
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.
CoRR, 2018
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval.
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation.
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015