Yuejie Chi

Carnegie Mellon University

Selected Tutorials

Generative Priors in Data Science: From Low-rank to Diffusion Models, NASIT 2024.
Information-theoretic, Statistical and Algorithmic Foundations of Reinforcement Learning, ISIT 2024.
Statistical and Algorithmic Foundations of Reinforcement Learning, JSM 2023.
Non-asymptotic Analysis for Reinforcement Learning, SIGMETRICS 2023.
Advances in Federated Optimization: Efficiency, Resiliency, and Privacy, ICASSP 2023.
Reinforcement Learning: Fundamentals, Algorithms, and Theory, ICASSP 2022.
Scalable and Robust Nonconvex Approaches for Low-rank Structure Estimation, International Workshop on Intelligent Signal Processing, 2021.
Nonconvex Optimization for High-Dimensional Signal Estimation: Spectral and Iterative Methods, EUSIPCO 2020.
Nonconvex Optimization Meets Low-Rank Matrix Factorization, accompanying slides of an overview paper with the same title.
Taming Nonconvexity in Information Science, ITW 2018.
Recent Advances in Nonconvex Methods for High-Dimensional Estimation, ICASSP 2018.
Convex Optimization Techniques for Super-resolution Parameter Estimation, ICASSP 2016.
Compressive Parameter Estimation: The Good, The Bad, and The Ugly, SSP 2014.

Selected Plenary and Keynote Talks

Fantastic Diffusion Models and Where to Apply Them, IEEE Information Theory Workshop, 2024.
Solving Inverse Problems with Generative Priors: From Low-rank to Diffusion Models, NIST/IEEE Conference on Computational Imaging Using Synthetic Apertures, 2024.
A Tale of Preconditioning and Overparameterization in Ill-conditioned Low-rank Estimation, CAMDA Conference, 2023.
Understanding the Efficacy of Reinforcement Learning Through a Non-asymptotic Lens, IEEE Data Science and Learning Workshop, 2022.
Model-Free RL: Non-asymptotic Statistical and Computational Guarantees, MIT LIDS Student Conference, 2022. [Video]
Non-asymptotic Statistical and Computational Guarantees of Reinforcement Learning Algorithms, Goldsmith Lecture, IEEE East Asian School of Information Theory, 2021.
Nonconvex Low-Rank Matrix Estimation: Geometry, Robustness, and Acceleration, SIAM Conference on Imaging Science, 2020. [Video]
Geometry and Regularization in Nonconvex Low-Rank Estimation, Signal Processing with Adaptive Sparse Structured Representations (SPARS) Workshop, 2019.

Selected Research Talks