Yuxin Chen
Openings
I'm looking for highly motivated postdocs and Ph. D. students with strong mathematical background and interest in machine learning theory (particularly diffusion models, and LLM), statistics, and optimization.
Recent news

 Yuchen Zhou joined UIUC
as an Assistant Professor in July 2024. Congrats, Yuchen!
 Hong Hu joined WUSTL
as an Assistant Professor in August 2024. Congrats, Hong!
 Joshua Agterberg joined UIUC
as an Assistant Professor in August 2024. Congrats, Joshua!
 Yuling Yan joined UWMadison as an Assistant Professor in August 2024. Congrats, Yuling!
 Yuling Yan received the IMS Lawrence D. Brown Ph. D. Student Award and the ICCM Best Thesis Award (silver medal). Congrats, Yuling!

Topic courses I have developed
Selected recent papers

Z. Huang, Y. Wei, Y. Chen, “Denoising diffusion probabilistic models are optimally adaptive to unknown low dimensionality,” 2024.
G. Li, Y. Wei, Y. Chi, Y. Chen, “A sharp convergence theory for
the probability flow ODEs of diffusion models,” 2024. [slides]
G. Li*, Y. Huang*, T. Efimov, Y. Wei, Y. Chi, Y. Chen, “Accelerating convergence of scorebased diffusion models, provably,” 2024 (*=equal contributions; accepted in part to ICML 2024). [slides]
Reinforcement learning
Z. Zhang, Y. Chen, J. D. Lee, S. S. Du, “Settling the sample complexity of online reinforcement learning,” 2023 (accepted in part to COLT 2024). [slides]
G. Li, Y. Yan, Y. Chen, J. Fan, “Minimaxoptimal rewardagnostic exploration in reinforcement learning,” 2023 (accepted in part to COLT 2024). [slides]
G. Li, L. Shi, Y. Chen, Y. Chi, Y. Wei, “Settling the sample complexity of modelbased offline reinforcement learning,” Annals of Statistics, vol. 52, no. 1, pp. 233260, 2024. [paper][AoS version]
G. Li, Y. Chi, Y. Wei, Y. Chen, “Minimaxoptimal multiagent RL in Markov games with a generative model,” NeurIPS 2022 (selected as oral).
G. Li, Y. Wei, Y. Chi, Y. Chen, “Softmax policy gradient methods can take exponential time to converge,” Mathematical Programming, vol. 201, pp. 707802, 2023 (appeared in part to COLT 2021). [paper][MP version][slides]
G. Li, C. Cai, Y. Chen, Y. Wei, Y. Chi, “Is QLearning minimax optimal? A tight sample complexity analysis,” Operations Research, vol. 72, no. 1, pp. 203221, 2024 (appeared in part to ICML 2021). [paper][OR version]
S. Cen, C. Cheng, Y. Chen, Y. Wei, Y. Chi, “Fast global convergence of natural policy gradient methods with entropy regularization,” Operations Research, vol. 70, no. 4, pp. 2563–2578, 2022 (INFORMS George Nicholson award finalist, 2021). [ArXiv][OR version][slides]
G. Li, Y. Wei, Y. Chi, Y. Chen, “Breaking the sample size barrier in modelbased reinforcement learning with a generative model,” Operations Research, vol. 72, no. 1, pp. 222236, 2024 (appeared in part to NeurIPS 2020). [paper][OR version][slides]
Spectral methods
Y. Zhou, Y. Chen, “Deflated HeteroPCA: Overcoming the curse of illconditioning in heteroskedastic PCA,” accepted to Annals of Statistics, 2024+. [ArXiv][slides]
Y. Yan, Y. Chen, J. Fan, “Inference for heteroskedastic PCA with missing data,” Annals of Statistics, vol. 52, no. 2, pp. 729756, 2024. [ArXiv][AoS version][slides]
C. Cai, G. Li, Y. Chi, H. V. Poor, Y. Chen, “Subspace estimation from unbalanced and incomplete data matrices, $\ell_{2,\infty}$ statistical guarantees ” Annals of Statistics, vol. 49, no. 2, pp. 944967, 2021. [ArXiv][AoS version]
Y. Chen, C. Cheng, J. Fan, “Asymmetry helps: Eigenvalue and eigenvector analyses of asymmetrically perturbed lowrank matrices,” Annals of Statistics, vol. 49, no. 1, pp. 435458, 2021. [ArXiv][AoS version][slides]
Y. Chen, J. Fan, C. Ma, K. Wang, “Spectral method and regularized MLE are both optimal for topK ranking,” Annals of Statistics, vol. 47, no. 4, pp. 22042235, August 2019. [ArXiv][AoS version][slides]
