I am a PhD student in the Computer Sciences Department at the University of Wisconsin–Madison. I am fortunate to be advised by Prof. Ilias Diakonikolas. I am working on theoretical machine learning and robust statistics.

Before coming to Madison, I did my undergraduate studies in Greece, at the National Technical University of Athens.

Feel free to contact me at: `pittas[at]wisc.edu` or `pittas.than[at]gmail.com`.

I am a PhD student in the Computer Sciences Department at the University of Wisconsin–Madison. I am fortunate to be advised by Prof. Ilias Diakonikolas. I am working on theoretical machine learning and robust statistics.

Before coming to Madison, I did my undergraduate studies in Greece, at the National Technical University of Athens.

Feel free to contact me at: `pittas[at]wisc.edu` or `pittas.than[at]gmail.com`.

**Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation**

with Ilias Diakonikolas, Daniel M. Kane, and Jasper C.H. Lee

*Manuscript, 2023*

[Abstract] [arXiv]**Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression**

with Ilias Diakonikolas, Daniel M. Kane, and Ankit Pensia

*Advances in Neural Information Processing Systems (NeurIPS), 2023*

[Abstract] [arXiv]**A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm**

with Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, and Ankit Pensia

*Advances in Neural Information Processing Systems (NeurIPS), 2023*

**Spotlight Presentation**

[Abstract] [arXiv]**SQ Lower Bounds for Learning Bounded Covariance GMMs**

with Ilias Diakonikolas, Daniel M. Kane, and Nikos Zarifis

*Conference on Learning Theory (COLT), 2023*

[Abstract] [arXiv]**Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA**

with Ilias Diakonikolas, Daniel M. Kane, and Ankit Pensia

*International Conference on Machine Learning (ICML), 2023*

[Abstract] [arXiv]**List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering**

with Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, and Ankit Pensia

*Advances in Neural Information Processing Systems (NeurIPS), 2022*

**Oral Presentation**

[Abstract] [arXiv]**Robust Sparse Mean Estimation via Sum of Squares**

with Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, and Ankit Pensia

*Conference on Learning Theory (COLT), 2022*

[Abstract] [arXiv]**Streaming Algorithms for High-Dimensional Robust Statistics**

with Ilias Diakonikolas, Daniel M. Kane, and Ankit Pensia

*International Conference on Machine Learning (ICML), 2022*

[Abstract] [arXiv]**Statistical Query Lower Bounds for List-Decodable Linear Regression**

with Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, and Alistair Stewart

*Advances in Neural Information Processing Systems (NeurIPS), 2021*

**Spotlight Presentation**

[Abstract] [arXiv]**The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals**

with Ilias Diakonikolas, Daniel M. Kane, and Nikos Zarifis

*Conference on Learning Theory (COLT), 2021*

[Abstract] [arXiv]**Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries**

with Dimitris Fotakis and Stratis Skoulakis

*AAAI Conference on Artificial Intelligence, 2021*

[Abstract] [Conference version]

- Grader for Introduction to Computational Learning Theory, UW-Madison, 2023
- Teaching Assistant for Introduction to Artificial Inteligence, UW-Madison, 2022
- Teaching Assistant for Discrete Mathematics, NTUA, 2019
- Teaching Assistant for Algorithms and Complexity, NTUA, 2019
- Lab Assistant for Introduction to Programming, NTUA, 2019
**Reviewer:**NeurIPS 2023, ICLR 2023, NeurIPS 2022, ICML 2022