Allen Liu

Orcid: 0000-0001-7987-5755

According to our database1, Allen Liu authored at least 33 papers between 2018 and 2024.

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Bibliography

2024
High-Temperature Gibbs States are Unentangled and Efficiently Preparable.
CoRR, 2024

An optimal tradeoff between entanglement and copy complexity for state tomography.
CoRR, 2024

2023
Robustly Learning General Mixtures of Gaussians.
J. ACM, June, 2023

Learning quantum Hamiltonians at any temperature in polynomial time.
CoRR, 2023

A New Approach to Learning Linear Dynamical Systems.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Robust Voting Rules from Algorithmic Robust Statistics.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Constant Approximation for Individual Preference Stable Clustering.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems.
Proceedings of the International Conference on Machine Learning, 2023

Matrix Completion in Almost-Verification Time.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

When Does Adaptivity Help for Quantum State Learning?
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Semi-Random Sparse Recovery in Nearly-Linear Time.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Tight Bounds for State Tomography with Incoherent Measurements.
CoRR, 2022

Clustering mixtures with almost optimal separation in polynomial time.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Robust Model Selection and Nearly-Proper Learning for GMMs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minimax Rates for Robust Community Detection.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Tight Bounds for Quantum State Certification with Incoherent Measurements.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Learning GMMs with Nearly Optimal Robustness Guarantees.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Sparsification for Sums of Exponentials and its Algorithmic Applications.
CoRR, 2021

How to Decompose a Tensor with Group Structure.
CoRR, 2021

Settling the robust learnability of mixtures of Gaussians.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Optimal Contextual Pricing and Extensions.
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, 2021

Variable Decomposition for Prophet Inequalities and Optimal Ordering.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Margin-Independent Online Multiclass Learning via Convex Geometry.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Distributed Load Balancing: A New Framework and Improved Guarantees.
Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021

2020
Fourier and Circulant Matrices are Not Rigid.
Theory Comput., 2020

Competing Optimally Against An Imperfect Prophet.
CoRR, 2020

Contextual Search for General Hypothesis Classes.
CoRR, 2020

Tensor Completion Made Practical.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Myersonian Regression.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation.
Proceedings of the Conference on Learning Theory, 2020

2018
Efficiently Learning Mixtures of Mallows Models.
Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018


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