| 2025 | COLT | Online Covariance Estimation in Nonsmooth Stochastic Approximation. | Liwei Jiang, Abhishek Roy, Krishna Balasubramanian, Damek Davis, Dmitriy Drusvyatskiy, Sen Na |
| 2025 | ICLR | Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent. | Sayan Banerjee, Krishna Balasubramanian, Promit Ghosal |
| 2025 | ICLR | Transformers Handle Endogeneity in In-Context Linear Regression. | Haodong Liang, Krishna Balasubramanian, Lifeng Lai |
| 2025 | UAI | Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps. | Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik |
| 2024 | AISTATS | Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression. | Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik |
| 2023 | COLT | Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincar Inequality. | Alireza Mousavi-Hosseini, Tyler K. Farghly, Ye He, Krishna Balasubramanian, Murat A. Erdogdu |
| 2023 | COLT | Improved Discretization Analysis for Underdamped Langevin Monte Carlo. | Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu |
| 2023 | ICML | Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity. | Xuxing Chen, Minhui Huang, Shiqian Ma, Krishna Balasubramanian |
| 2023 | ICML | Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space. | Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim |
| 2022 | COLT | Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. | Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang |
| 2022 | UAI | High-probability bounds for robust stochastic Frank-Wolfe algorithm. | Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee |