| 2026 | STOC | Rigorous Implications of the Low-Degree Heuristic. | Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel |
| 2025 | STOC | Sample-Optimal Private Regression in Polynomial Time. | Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel |
| 2025 | STOC | Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations. | Kiril Bangachev, Guy Bresler, Stefan Tiegel, Vinod Vaikuntanathan |
| 2025 | STOC | SoS Certifiability of Subgaussian Distributions and Its Algorithmic Applications. | Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel |
| 2025 | STOC | SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More. | Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel |
| 2024 | COLT | Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. | Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel |
| 2024 | COLT | Improved Hardness Results for Learning Intersections of Halfspaces. | Stefan Tiegel |
| 2023 | COLT | Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems. | Stefan Tiegel |
| 2022 | COLT | Fast algorithm for overcomplete order-3 tensor decomposition. | Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, David Steurer, Stefan Tiegel |
| 2022 | COLT | Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise. | Rajai Nasser, Stefan Tiegel |
| 2021 | SODA | SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation. | David Steurer, Stefan Tiegel |
| 2019 | SODA | A Framework for Searching in Graphs in the Presence of Errors. | Dariusz Dereniowski, Stefan Tiegel, Przemyslaw Uznanski, Daniel Wolleb-Graf |