Stefan Tiegel

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Mixed Membership

Threshold Functions

Top Venues

Publications

Stefan Tiegel
Improved Hardness Results for Learning Intersections of Halfspaces. CoRR (2024)
Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel
Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. CoRR (2024)
Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel
Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. COLT (2024)
Stefan Tiegel
Improved Hardness Results for Learning Intersections of Halfspaces. COLT (2024)
Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang
Robust Mixture Learning when Outliers Overwhelm Small Groups. CoRR (2024)
Lucas Slot, Stefan Tiegel, Manuel Wiedmer
Testably Learning Polynomial Threshold Functions. CoRR (2024)
Stefan Tiegel
Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems. COLT (2023)
Gleb Novikov, David Steurer, Stefan Tiegel
Robust Mean Estimation Without a Mean: Dimension-Independent Error in Polynomial Time for Symmetric Distributions. CoRR (2023)
Gleb Novikov, David Steurer, Stefan Tiegel
Robust Mean Estimation Without Moments for Symmetric Distributions. NeurIPS (2023)
Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
Private estimation algorithms for stochastic block models and mixture models. NeurIPS (2023)
Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
Private estimation algorithms for stochastic block models and mixture models. CoRR (2023)
Stefan Tiegel
Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems. CoRR (2022)
Rajai Nasser, Stefan Tiegel
Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise. COLT (2022)
Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, Stefan Tiegel, David Steurer
Fast algorithm for overcomplete order-3 tensor decomposition. CoRR (2022)
Rajai Nasser, Stefan Tiegel
Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise. CoRR (2022)
Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, David Steurer, Stefan Tiegel
Fast algorithm for overcomplete order-3 tensor decomposition. COLT (2022)
Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. NeurIPS (2021)
David Steurer, Stefan Tiegel
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation. SODA (2021)
David Steurer, Stefan Tiegel
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation. CoRR (2021)
Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. CoRR (2021)
Dariusz Dereniowski, Stefan Tiegel, Przemyslaw Uznanski, Daniel Wolleb-Graf
A Framework for Searching in Graphs in the Presence of Errors. SOSA (2019)
Dariusz Dereniowski, Daniel Graf, Stefan Tiegel, Przemyslaw Uznanski
A Framework for Searching in Graphs in the Presence of Errors. CoRR (2018)