3 papers
quant-ph2026
Hierarchical Fourier Approximation for Variational Quantum Distribution Learning
Taha Hoseinpour Asli, Sajjad Hashemian, Ebrahim Ardeshir-Larijani
We study variational quantum distribution learning through a hierarchy of Walsh--Fourier approximations on the Boolean cube. At each level, a selected set of target Fourier coeffic…
cs.LG2025
List-Decodable Regression via Expander Sketching
Herbod Pourali, Sajjad Hashemian, Ebrahim Ardeshir-Larijani
We introduce an expander-sketching framework for list-decodable linear regression that achieves sample complexity , list size , and near input-s…
cs.LG2024
Optimal Bound for PCA with Outliers using Higher-Degree Voronoi Diagrams
Sajjad Hashemian, Mohammad Saeed Arvenaghi, Ebrahim Ardeshir-Larijani
In this paper, we introduce new algorithms for Principal Component Analysis (PCA) with outliers. Utilizing techniques from computational geometry, specifically higher-degree Vorono…