| An analysis of constant step size sgd in the non-convex regime: Asymptotic normality and bias L Yu, K Balasubramanian, S Volgushev, MA Erdogdu Advances in Neural Information Processing Systems 34, 4234-4248, 2021 | 43 | 2021 |
| Oracle inequalities for high-dimensional prediction J Lederer, L Yu, I Gaynanova Bernoulli 25 (2), 1225-1255, 2019 | 40 | 2019 |
| Mirror descent strikes again: Optimal stochastic convex optimization under infinite noise variance NM Vural, L Yu, K Balasubramanian, S Volgushev, MA Erdogdu Conference on Learning Theory, 65-102, 2022 | 25 | 2022 |
| False discovery rates in biological networks L Yu, T Kaufmann, J Lederer International Conference on Artificial Intelligence and Statistics, 163-171, 2021 | 8 | 2021 |
| Spectral clustering with variance information for group structure estimation in panel data L Yu, J Gu, S Volgushev Journal of Econometrics 241 (1), 105709, 2024 | 5* | 2024 |
| Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited L Yu, A Karagulyan, AS Dalalyan The Twelfth International Conference on Learning Representations, 2024 | 3 | 2024 |
| Parallelized Midpoint Randomization for Langevin Monte Carlo L Yu, A Dalalyan arXiv preprint arXiv:2402.14434, 2024 | 2 | 2024 |
| Log-Concave Sampling on Compact Supports: A Versatile Proximal Framework L Yu arXiv preprint arXiv:2405.15379, 2024 | | 2024 |
| Latent Structure Estimation for Panel Data and Theoretical Guarantees for Stochastic Optimization L Yu University of Toronto (Canada), 2022 | | 2022 |
