Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries. - Dimitris Fotakis 001; Thanasis Pittas; Stratis Skoulakis (AAAI, 2021)

The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model. - Ilias Diakonikolas; Daniel M. Kane; Thanasis Pittas; Nikos Zarifis (COLT, 2021)

Statistical Query Lower Bounds for List-Decodable Linear Regression. - Ilias Diakonikolas; Daniel Kane 001; Ankit Pensia; Thanasis Pittas; Alistair Stewart (NeurIPS, 2021)

The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals. - Ilias Diakonikolas; Daniel M. Kane; Thanasis Pittas; Nikos Zarifis (CoRR, 2021)

Robust Sparse Mean Estimation via Sum of Squares. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (COLT, 2022)

Streaming Algorithms for High-Dimensional Robust Statistics. - Ilias Diakonikolas; Daniel M. Kane; Ankit Pensia; Thanasis Pittas (ICML, 2022)

List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. - Ilias Diakonikolas; Daniel Kane 001; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (NeurIPS, 2022)

SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians. - Ilias Diakonikolas; Daniel M. Kane; Thanasis Pittas; Nikos Zarifis (COLT, 2023)

Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA. - Ilias Diakonikolas; Daniel Kane 001; Ankit Pensia; Thanasis Pittas (ICML, 2023)

A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. - Ilias Diakonikolas; Daniel Kane 001; Jasper C. H. Lee; Ankit Pensia; Thanasis Pittas (NeurIPS, 2023)

Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. - Ilias Diakonikolas; Daniel Kane 001; Ankit Pensia; Thanasis Pittas (NeurIPS, 2023)

SQ Lower Bounds for Learning Bounded Covariance GMMs. - Ilias Diakonikolas; Daniel M. Kane; Thanasis Pittas; Nikos Zarifis (CoRR, 2023)

Statistical Query Lower Bounds for Learning Truncated Gaussians. - Ilias Diakonikolas; Daniel M. Kane; Thanasis Pittas; Nikos Zarifis (COLT, 2024)

Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. - Ilias Diakonikolas; Daniel Kane 001; Sushrut Karmalkar; Ankit Pensia; Thanasis Pittas (ICML, 2024)

Optimal Robust Estimation under Local and Global Corruptions: Stronger Adversary and Smaller Error. - Thanasis Pittas; Ankit Pensia (COLT, 2025)

Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation. - Ilias Diakonikolas; Daniel M. Kane; Jasper C. H. Lee; Thanasis Pittas (SODA, 2025)

Entangled Mean Estimation in High Dimensions. - Ilias Diakonikolas; Daniel M. Kane; Sihan Liu; Thanasis Pittas (STOC, 2025)

Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination. - Ilias Diakonikolas; Giannis Iakovidis; Daniel M. Kane; Thanasis Pittas (CoRR, 2025)

Batch List-Decodable Linear Regression via Higher Moments. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Sihan Liu; Thanasis Pittas (CoRR, 2025)

On Learning Parallel Pancakes with Mostly Uniform Weights. - Ilias Diakonikolas; Daniel M. Kane; Sushrut Karmalkar; Jasper C. H. Lee; Thanasis Pittas (CoRR, 2025)

On Fine-Grained Distinct Element Estimation. - Ilias Diakonikolas; Daniel M. Kane; Jasper C. H. Lee; Thanasis Pittas; David P. Woodruff; Samson Zhou (CoRR, 2025)