Quantum-inspired classical algorithms for principal component analysis and supervised clustering. - Ewin Tang (CoRR, 2018)

Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension. - András Gilyén; Seth Lloyd; Ewin Tang (CoRR, 2018)

A quantum-inspired classical algorithm for recommendation systems. - Ewin Tang (Electron. Colloquium Comput. Complex., 2018)

Quantum-Inspired Algorithms for Solving Low-Rank Linear Equation Systems with Logarithmic Dependence on the Dimension. - Nai-Hui Chia; András Gilyén; Han-Hsuan Lin; Seth Lloyd; Ewin Tang; Chunhao Wang (ISAAC, 2020)

Demo: Visualizing USSD and IVR Usage Data with Icicle Charts. - Matt Ziegler; Galen Weld; Ewin Tang; Maureen Daum (COMPASS, 2022)

Optimal learning of quantum Hamiltonians from high-temperature Gibbs states. - Jeongwan Haah; Robin Kothari; Ewin Tang (FOCS, 2022)

Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning. - Nai-Hui Chia; András Pal Gilyén; Tongyang Li; Han-Hsuan Lin; Ewin Tang; Chunhao Wang (J. ACM, 2022)

An improved quantum-inspired algorithm for linear regression. - András Gilyén; Zhao Song 002; Ewin Tang (Quantum, 2022)

Query-optimal estimation of unitary channels in diamond distance. - Jeongwan Haah; Robin Kothari; Ryan O'Donnell; Ewin Tang (FOCS, 2023)

Do you know what q-means? - João F. Doriguello; Alessandro Luongo; Ewin Tang (CoRR, 2023)

Quantum Machine Learning Without Any Quantum - Ewin Tang (2023)

High-Temperature Gibbs States are Unentangled and Efficiently Preparable. - Ainesh Bakshi; Allen Liu; Ankur Moitra; Ewin Tang (FOCS, 2024)

Structure Learning of Hamiltonians from Real-Time Evolution. - Ainesh Bakshi; Allen Liu; Ankur Moitra; Ewin Tang (FOCS, 2024)

An Improved Classical Singular Value Transformation for Quantum Machine Learning. - Ainesh Bakshi; Ewin Tang (SODA, 2024)

A CS guide to the quantum singular value transformation. - Ewin Tang; Kevin Tian (SOSA, 2024)

Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. - Ainesh Bakshi; Allen Liu; Ankur Moitra; Ewin Tang (STOC, 2024)

Learning the Closest Product State. - Ainesh Bakshi; John Bostanci; William Kretschmer; Zeph Landau; Jerry Li 001; Allen Liu; Ryan O'Donnell; Ewin Tang (STOC, 2025)

Beating full state tomography for unentangled spectrum estimation. - Angelos Pelecanos; Xinyu Tan; Ewin Tang; John Wright (CoRR, 2025)

Amplitude amplification and estimation require inverses. - Ewin Tang; John Wright (CoRR, 2025)