Allen Liu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 55

Top Topics

Pareto Frontier

Mixtures Of Gaussians

Robust Statistics

Top Venues

Publications

Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Structure learning of Hamiltonians from real-time evolution. CoRR (2024)
Sitan Chen, Jerry Li, Allen Liu
An Optimal Tradeoff between Entanglement and Copy Complexity for State Tomography. STOC (2024)
Sitan Chen, Jerry Li, Allen Liu
Optimal high-precision shadow estimation. CoRR (2024)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. STOC (2024)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
High-Temperature Gibbs States are Unentangled and Efficiently Preparable. CoRR (2024)
Sitan Chen, Jerry Li, Allen Liu
An optimal tradeoff between entanglement and copy complexity for state tomography. CoRR (2024)
Allen Liu, Ankur Moitra
Robustly Learning General Mixtures of Gaussians. J. ACM 70 (3) (2023)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
A New Approach to Learning Linear Dynamical Systems. CoRR (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang
Learning quantum Hamiltonians at any temperature in polynomial time. CoRR (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. CoRR (2023)
Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. FOCS (2023)
Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. CoRR (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. FOCS (2023)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke
When Does Adaptivity Help for Quantum State Learning? FOCS (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. ICML (2023)
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Constant Approximation for Individual Preference Stable Clustering. NeurIPS (2023)
Allen Liu, Ankur Moitra
Robust Voting Rules from Algorithmic Robust Statistics. SODA (2023)
Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau
A New Approach to Learning Linear Dynamical Systems. STOC (2023)
Allen Liu, Mark Sellke
The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication. COLT (2022)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu
Tight Bounds for Quantum State Certification with Incoherent Measurements. CoRR (2022)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke
Tight Bounds for State Tomography with Incoherent Measurements. CoRR (2022)
Allen Liu, Ankur Moitra
Minimax Rates for Robust Community Detection. FOCS (2022)
Allen Liu, Ankur Moitra
Learning GMMs with Nearly Optimal Robustness Guarantees. COLT (2022)
Allen Liu, Ankur Moitra
Minimax Rates for Robust Community Detection. CoRR (2022)
Allen Liu, Jerry Li, Ankur Moitra
Robust Model Selection and Nearly-Proper Learning for GMMs. NeurIPS (2022)
Sitan Chen, Jerry Li, Brice Huang, Allen Liu
Tight Bounds for Quantum State Certification with Incoherent Measurements. FOCS (2022)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR (2022)
Allen Liu, Mark Sellke
The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication. CoRR (2022)
Allen Liu, Jerry Li
Clustering mixtures with almost optimal separation in polynomial time. STOC (2022)
Allen Liu, Renato Paes Leme, Jon Schneider
Optimal Contextual Pricing and Extensions. SODA (2021)
Sara Ahmadian, Allen Liu, Binghui Peng, Morteza Zadimoghaddam
Distributed Load Balancing: A New Framework and Improved Guarantees. ITCS (2021)
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang
Margin-Independent Online Multiclass Learning via Convex Geometry. NeurIPS (2021)
Allen Liu, Ankur Moitra
Robust Voting Rules from Algorithmic Robust Statistics. CoRR (2021)
Allen Liu, Ankur Moitra
Learning GMMs with Nearly Optimal Robustness Guarantees. CoRR (2021)
Allen Liu, Ankur Moitra
Settling the robust learnability of mixtures of Gaussians. STOC (2021)
Jerry Li, Allen Liu, Ankur Moitra
Sparsification for Sums of Exponentials and its Algorithmic Applications. CoRR (2021)
Allen Liu, Ankur Moitra
How to Decompose a Tensor with Group Structure. CoRR (2021)
Allen Liu, Renato Paes Leme, Martin Pál, Jon Schneider, Balasubramanian Sivan
Variable Decomposition for Prophet Inequalities and Optimal Ordering. EC (2021)
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang
Margin-Independent Online Multiclass Learning via Convex Geometry. CoRR (2021)
Jerry Li, Allen Liu
Clustering Mixtures with Almost Optimal Separation in Polynomial Time. CoRR (2021)
Allen Liu, Renato Paes Leme, Jon Schneider
Myersonian Regression. NeurIPS (2020)
Zeev Dvir, Allen Liu
Fourier and Circulant Matrices are Not Rigid. Theory Comput. 16 (2020)
Allen Liu, Ankur Moitra
Tensor Completion Made Practical. CoRR (2020)
Allen Liu, Renato Paes Leme, Martin Pal, Jon Schneider, Balasubramanian Sivan
Competing Optimally Against An Imperfect Prophet. CoRR (2020)
Allen Liu, Ankur Moitra
Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation. COLT (2020)
Allen Liu, Renato Paes Leme, Jon Schneider
Contextual Search for General Hypothesis Classes. CoRR (2020)
Allen Liu, Ankur Moitra
Settling the Robust Learnability of Mixtures of Gaussians. CoRR (2020)
Allen Liu, Ankur Moitra
Tensor Completion Made Practical. NeurIPS (2020)
Zeev Dvir, Allen Liu
Fourier and Circulant Matrices are Not Rigid. CoRR (2019)
Zeev Dvir, Allen Liu
Fourier and Circulant Matrices Are Not Rigid. Computational Complexity Conference (2019)
Zeev Dvir, Allen Liu
Fourier and Circulant Matrices are Not Rigid. Electron. Colloquium Comput. Complex. 26 (2019)
Allen Liu, Ankur Moitra
Efficiently Learning Mixtures of Mallows Models. CoRR (2018)
Allen Liu, Ankur Moitra
Efficiently Learning Mixtures of Mallows Models. FOCS (2018)