Stefan Tiegel - RankMe

34 papers A* 15Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Rigorous Implications of the Low-Degree Heuristic. CoRR Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel
2025	J	`jnl`	Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point. CoRR Hongjie Chen, Jingqiu Ding, Yiding Hua, Stefan Tiegel
2025	A*	`conf`	Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations. STOC Kiril Bangachev, Guy Bresler, Stefan Tiegel, Vinod Vaikuntanathan
2025	A*	`conf`	Sample-Optimal Private Regression in Polynomial Time. STOC Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel
2025	J	`jnl`	Sample-Optimal Private Regression in Polynomial Time. CoRR Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel
2025	A*	`conf`	SoS Certifiability of Subgaussian Distributions and Its Algorithmic Applications. STOC Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2025	A*	`conf`	SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More. STOC Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2024	A*	`conf`	Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. COLT Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel
2024	J	`jnl`	Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression. CoRR Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel
2024	A*	`conf`	Improved Hardness Results for Learning Intersections of Halfspaces. COLT Stefan Tiegel
2024	J	`jnl`	Improved Hardness Results for Learning Intersections of Halfspaces. CoRR Stefan Tiegel
2024	J	`jnl`	Near-Optimal Time-Sparsity Trade-Offs for Solving Noisy Linear Equations. CoRR Kiril Bangachev, Guy Bresler, Stefan Tiegel, Vinod Vaikuntanathan
2024	A*	`conf`	Robust Mixture Learning when Outliers Overwhelm Small Groups. NeurIPS Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang
2024	J	`jnl`	Robust Mixture Learning when Outliers Overwhelm Small Groups. CoRR Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang
2024	J	`jnl`	SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications. CoRR Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2024	J	`jnl`	SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More. CoRR Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2024	A*	`conf`	Testably Learning Polynomial Threshold Functions. NeurIPS Lucas Slot, Stefan Tiegel, Manuel Wiedmer
2024	J	`jnl`	Testably Learning Polynomial Threshold Functions. CoRR Lucas Slot, Stefan Tiegel, Manuel Wiedmer
2023	A*	`conf`	Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems. COLT Stefan Tiegel
2023	A*	`conf`	Private estimation algorithms for stochastic block models and mixture models. NeurIPS Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
2023	J	`jnl`	Private estimation algorithms for stochastic block models and mixture models. CoRR Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel
2023	A*	`conf`	Robust Mean Estimation Without Moments for Symmetric Distributions. NeurIPS Gleb Novikov, David Steurer, Stefan Tiegel
2023	J	`jnl`	Robust Mean Estimation Without a Mean: Dimension-Independent Error in Polynomial Time for Symmetric Distributions. CoRR Gleb Novikov, David Steurer, Stefan Tiegel
2022	A*	`conf`	Fast algorithm for overcomplete order-3 tensor decomposition. COLT Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, David Steurer, Stefan Tiegel
2022	J	`jnl`	Fast algorithm for overcomplete order-3 tensor decomposition. CoRR Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, Stefan Tiegel, David Steurer
2022	J	`jnl`	Hardness of Agnostically Learning Halfspaces from Worst-Case Lattice Problems. CoRR Stefan Tiegel
2022	A*	`conf`	Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise. COLT Rajai Nasser, Stefan Tiegel
2022	J	`jnl`	Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise. CoRR Rajai Nasser, Stefan Tiegel
2021	A*	`conf`	Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. NeurIPS Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
2021	J	`jnl`	Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers. CoRR Tommaso d'Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
2021	A*	`conf`	SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation. SODA David Steurer, Stefan Tiegel
2021	J	`jnl`	SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation. CoRR David Steurer, Stefan Tiegel
2019	—	`conf`	A Framework for Searching in Graphs in the Presence of Errors. SOSA Dariusz Dereniowski, Stefan Tiegel, Przemyslaw Uznanski, Daniel Wolleb-Graf
2018	J	`jnl`	A Framework for Searching in Graphs in the Presence of Errors. CoRR Dariusz Dereniowski, Daniel Graf, Stefan Tiegel, Przemyslaw Uznanski