Tiegel, Stefan

11 publications

NeurIPS 2025 Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point Hongjie Chen, Jingqiu Ding, Yiding Hua, Stefan Tiegel

COLT 2024 Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel

COLT 2024 Improved Hardness Results for Learning Intersections of Halfspaces Stefan Tiegel

NeurIPS 2024 Robust Mixture Learning When Outliers Overwhelm Small Groups Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang

NeurIPS 2024 Testably Learning Polynomial Threshold Functions Lucas Slot, Stefan Tiegel, Manuel Wiedmer

COLT 2023 Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems Stefan Tiegel

NeurIPS 2023 Private Estimation Algorithms for Stochastic Block Models and Mixture Models Hongjie Chen, Vincent Cohen-Addad, Tommaso d’Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel

NeurIPS 2023 Robust Mean Estimation Without Moments for Symmetric Distributions Gleb Novikov, David Steurer, Stefan Tiegel

COLT 2022 Fast Algorithm for Overcomplete Order-3 Tensor Decomposition Jingqiu Ding, Tommaso d’Orsi, Chih-Hung Liu, David Steurer, Stefan Tiegel

COLT 2022 Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise Rajai Nasser, Stefan Tiegel

NeurIPS 2021 Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel