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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Efstratios Tsoukanis
Visiting Scholar at the CGU Institute of Mathematical Sciences. Applied harmonic analysis and geometric machine learning.
publications
Relationships between the Phase Retrieval Problem and Permutation Invariant Embeddings
Published in 2023 International Conference on Sampling Theory and Applications (SampTA), 2023
Authors: Radu Balan, Efstratios Tsoukanis.
Recommended citation: R. Balan and E. Tsoukanis, "Relationships between the Phase Retrieval Problem and Permutation Invariant Embeddings," in 2023 International Conference on Sampling Theory and Applications (SampTA), Yale University, New Haven, CT, USA, 2023. https://ieeexplore.ieee.org/document/10301202/
G-Invariant Representations using Coorbits: Injectivity Properties
Published in arXiv preprint, 2023
Authors: Radu Balan, Efstratios Tsoukanis.
Recommended citation: R. Balan and E. Tsoukanis, "G-Invariant Representations using Coorbits: Injectivity Properties," arXiv:2310.16365, 2023. https://arxiv.org/abs/2310.16365
Stability of sorting based embeddings
Published in arXiv preprint, 2024
Authors: Radu Balan, Efstratios Tsoukanis, Matthias Wellershoff.
Recommended citation: R. Balan, E. Tsoukanis, and M. Wellershoff, "Stability of sorting based embeddings," arXiv:2410.05446, 2024. https://arxiv.org/abs/2410.05446
Active Learning Classification from a Signal Separation Perspective
Published in 2025 International Conference on Sampling Theory and Applications (SampTA), Vienna, Austria, 2025
Authors: Hrushikesh Mhaskar, Ryan O’Dowd, Efstratios Tsoukanis.
Recommended citation: H. N. Mhaskar, R. O'Dowd, and E. Tsoukanis, "Active Learning Classification from a Signal Separation Perspective," in 2025 International Conference on Sampling Theory and Applications (SampTA), Vienna, Austria, 2025. https://arxiv.org/abs/2502.16425
An Approximation Theory Perspective on Machine Learning
Published in Neural Networks (Elsevier), 2026
Authors: Hrushikesh N. Mhaskar, Efstratios Tsoukanis, Ameya D. Jagtap.
Recommended citation: H. N. Mhaskar, E. Tsoukanis, and A. D. Jagtap, "An Approximation Theory Perspective on Machine Learning," Neural Networks, art. 108841, 2026. https://www.sciencedirect.com/science/article/pii/S0893608026003035
Quantitative Bounds for Sorting-Based Permutation-Invariant Embeddings
Published in IEEE Transactions on Information Theory (accepted), 2026
Authors: Nadav Dym, Matthias Wellershoff, Efstratios Tsoukanis, Daniel Levy, Radu Balan.
Recommended citation: N. Dym, M. Wellershoff, E. Tsoukanis, D. Levy, and R. Balan, "Quantitative Bounds for Sorting-Based Permutation-Invariant Embeddings," IEEE Transactions on Information Theory, 2026 (to appear). https://arxiv.org/abs/2510.22186
G-Invariant Representations using Coorbits: Bi-Lipschitz Properties
Published in Advances in Computational Mathematics, 2026
Authors: Radu Balan, Efstratios Tsoukanis.
Recommended citation: R. Balan and E. Tsoukanis, "G-Invariant Representations using Coorbits: Bi-Lipschitz Properties," Advances in Computational Mathematics, vol. 52, no. 5, art. 92, 2026. https://arxiv.org/abs/2308.11784