| 2025 | COLT | Learning Mixtures of Gaussians Using Diffusion Models. | Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee |
| 2025 | COLT | Computing Optimal Regularizers for Online Linear Optimization. | Khashayar Gatmiry, Jon Schneider, Stefanie Jegelka |
| 2025 | ICLR | Rethinking Invariance in In-context Learning. | Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang |
| 2024 | AISTATS | EM for Mixture of Linear Regression with Clustered Data. | Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar |
| 2024 | COLT | Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. | Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala |
| 2024 | COLT | Adversarial Online Learning with Temporal Feedback Graphs. | Khashayar Gatmiry, Jon Schneider |
| 2024 | ICML | Simplicity Bias via Global Convergence of Sharpness Minimization. | Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka |
| 2024 | ICML | Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? | Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar |
| 2024 | SODA | Bandit Algorithms for Prophet Inequality and Pandora's Box. | Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang |
| 2023 | COLT | Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. | Zakaria Mhammedi, Khashayar Gatmiry |
| 2022 | ICLR | Optimization and Adaptive Generalization of Three layer Neural Networks. | Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner |