Learning discrete distributions: user vs item-level privacy. - Yuhan Liu 007; Ananda Theertha Suresh; Felix X. Yu; Sanjiv Kumar; Michael Riley 001 (NeurIPS, 2020)

Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints. - Jayadev Acharya; Yuhan Liu 007; Ziteng Sun (CoRR, 2020)

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints. - Jayadev Acharya; Peter Kairouz; Yuhan Liu 007; Ziteng Sun (ALT, 2021)

Interactive Inference under Information Constraints. - Jayadev Acharya; Clément L. Canonne; Yuhan Liu 007; Ziteng Sun; Himanshu Tyagi (ISIT, 2021)

Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition. - Jayadev Acharya; Clément L. Canonne; Yuhan Liu 007; Ziteng Sun; Himanshu Tyagi (NeurIPS, 2021)

Histogram Estimation under User-level Privacy with Heterogeneous Data. - Yuhan Liu 007; Ananda Theertha Suresh; Wennan Zhu; Peter Kairouz; Marco Gruteser (CoRR, 2022)

Discrete Distribution Estimation under User-level Local Differential Privacy. - Jayadev Acharya; Yuhan Liu 007; Ziteng Sun (AISTATS, 2023)

Algorithms for bounding contribution for histogram estimation under user-level privacy. - Yuhan Liu 007; Ananda Theertha Suresh; Wennan Zhu; Peter Kairouz; Marco Gruteser (ICML, 2023)

The role of randomness in quantum state certification with unentangled measurements. - Yuhan Liu 007; Jayadev Acharya (COLT, 2024)

The role of shared randomness in quantum state certification with unentangled measurements. - Yuhan Liu 007; Jayadev Acharya (CoRR, 2024)

Quantum state testing with restricted measurements. - Yuhan Liu 007; Jayadev Acharya (CoRR, 2024)

Pauli Measurements Are Not Optimal for Single-Copy Tomography. - Jayadev Acharya; Abhilash Dharmavarapu; Yuhan Liu 007; Nengkun Yu (STOC, 2025)

Pauli Measurements Are Near-Optimal for Single-Qubit Tomography. - Jayadev Acharya; Abhilash Dharmavarapu; Yuhan Liu 007; Nengkun Yu (CoRR, 2025)