Diana Halikias

According to our database, Diana Halikias authored at least 8 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Quasi-optimal hierarchically semi-separable matrix approximation.

Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson

CoRR, May, 2025

Near-optimal hierarchical matrix approximation from matrix-vector products.

Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson

Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, 2025

2024

Structured matrix recovery from matrix-vector products.

Diana Halikias, Alex Townsend

Numer. Linear Algebra Appl., January, 2024

Fixed-sparsity matrix approximation from matrix-vector products.

Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco

CoRR, 2024

Operator learning without the adjoint.

Nicolas Boullé, Diana Halikias, Samuel E. Otto, Alex Townsend

CoRR, 2024

2023

Elliptic PDE learning is provably data-efficient.

Nicolas Boullé, Diana Halikias, Alex Townsend

CoRR, 2023

2022

Matrix recovery from matrix-vector products.

Diana Halikias, Alex Townsend

CoRR, 2022

2021

Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks.

Annan Yu, Chloé Becquey, Diana Halikias, Matthew Esmaili Mallory, Alex Townsend

CoRR, 2021