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Thanasis Pittas

20 papers · 2021–2026 · 4 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

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Papers

A Quasi-Polynomial Time Mean Estimator Under Mean-Shift Contamination with Unknown Covariance COLT 2026 High-Dimensional Gaussian Mean Estimation under Realizable Contamination COLT 2026 Linear Regression under Missing or Corrupted Coordinates COLT 2026 Batch List-Decodable Linear Regression via Higher Moments ICML 2025 Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination ICML 2025 On Fine-Grained Distinct Element Estimation ICML 2025 On Learning Parallel Pancakes with Mostly Uniform Weights ICML 2025 Optimal Robust Estimation under Local and Global Corruptions: Stronger Adversary and Smaller Error COLT 2025 Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination ICML 2024 Statistical Query Lower Bounds for Learning Truncated Gaussians COLT 2024 A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm NeurIPS 2023 Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA ICML 2023 Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression NeurIPS 2023 SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians COLT 2023 List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering NeurIPS 2022 Robust Sparse Mean Estimation via Sum of Squares COLT 2022 Streaming Algorithms for High-Dimensional Robust Statistics ICML 2022 Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries AAAI 2021 Statistical Query Lower Bounds for List-Decodable Linear Regression NeurIPS 2021 The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model COLT 2021