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2020 – today
- 2024
[c28]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
High-Temperature Gibbs States are Unentangled and Efficiently Preparable. FOCS 2024: 1027-1036- [c27]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
Structure Learning of Hamiltonians from Real-Time Evolution. FOCS 2024: 1037-1050 - [c26]Sitan Chen
, Jerry Li, Allen Liu:
An Optimal Tradeoff between Entanglement and Copy Complexity for State Tomography. STOC 2024: 1331-1342 - [c25]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
Learning Quantum Hamiltonians at Any Temperature in Polynomial Time. STOC 2024: 1470-1477 - [i28]Sitan Chen, Jerry Li, Allen Liu:
An optimal tradeoff between entanglement and copy complexity for state tomography. CoRR abs/2402.16353 (2024) - [i27]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
High-Temperature Gibbs States are Unentangled and Efficiently Preparable. CoRR abs/2403.16850 (2024) - [i26]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
Structure learning of Hamiltonians from real-time evolution. CoRR abs/2405.00082 (2024) - [i25]Sitan Chen, Jerry Li, Allen Liu:
Optimal high-precision shadow estimation. CoRR abs/2407.13874 (2024) - 2023
- [j2]Allen Liu, Ankur Moitra:
Robustly Learning General Mixtures of Gaussians. J. ACM 70(3): 21:1-21:53 (2023) - [c24]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT 2023: 2352-2398 - [c23]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
When Does Adaptivity Help for Quantum State Learning? FOCS 2023: 391-404 - [c22]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. FOCS 2023: 2102-2128 - [c21]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: 2159-2168 - [c20]Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau:
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. ICML 2023: 1549-1563 - [c19]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. NeurIPS 2023 - [c18]Allen Liu, Ankur Moitra:
Robust Voting Rules from Algorithmic Robust Statistics. SODA 2023: 3471-3512 - [c17]Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau:
A New Approach to Learning Linear Dynamical Systems. STOC 2023: 335-348 - [i24]Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau:
A New Approach to Learning Linear Dynamical Systems. CoRR abs/2301.09519 (2023) - [i23]Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau:
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems. CoRR abs/2307.06538 (2023) - [i22]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 abs/2307.10273 (2023) - [i21]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. CoRR abs/2308.03661 (2023) - [i20]Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang:
Constant Approximation for Individual Preference Stable Clustering. CoRR abs/2309.16840 (2023) - [i19]Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang:
Learning quantum Hamiltonians at any temperature in polynomial time. CoRR abs/2310.02243 (2023) - 2022
- [c16]Allen Liu, Ankur Moitra:
Learning GMMs with Nearly Optimal Robustness Guarantees. COLT 2022: 2815-2895 - [c15]Allen Liu, Mark Sellke:
The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication. COLT 2022: 3094 - [c14]Allen Liu, Ankur Moitra:
Minimax Rates for Robust Community Detection. FOCS 2022: 823-831 - [c13]Sitan Chen, Jerry Li, Brice Huang, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. FOCS 2022: 1205-1213 - [c12]Allen Liu, Jerry Li, Ankur Moitra:
Robust Model Selection and Nearly-Proper Learning for GMMs. NeurIPS 2022 - [c11]Allen Liu, Jerry Li:
Clustering mixtures with almost optimal separation in polynomial time. STOC 2022: 1248-1261 - [i18]Allen Liu, Mark Sellke:
The Pareto Frontier of Instance-Dependent Guarantees in Multi-Player Multi-Armed Bandits with no Communication. CoRR abs/2202.09653 (2022) - [i17]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR abs/2203.04002 (2022) - [i16]Sitan Chen, Brice Huang, Jerry Li, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. CoRR abs/2204.07155 (2022) - [i15]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
Tight Bounds for State Tomography with Incoherent Measurements. CoRR abs/2206.05265 (2022) - [i14]Allen Liu, Ankur Moitra:
Minimax Rates for Robust Community Detection. CoRR abs/2207.11903 (2022) - 2021
- [c10]Sara Ahmadian, Allen Liu, Binghui Peng, Morteza Zadimoghaddam:
Distributed Load Balancing: A New Framework and Improved Guarantees. ITCS 2021: 79:1-79:20 - [c9]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. NeurIPS 2021: 29156-29167 - [c8]Allen Liu, Renato Paes Leme, Martin Pál, Jon Schneider, Balasubramanian Sivan:
Variable Decomposition for Prophet Inequalities and Optimal Ordering. EC 2021: 692 - [c7]Allen Liu, Renato Paes Leme, Jon Schneider:
Optimal Contextual Pricing and Extensions. SODA 2021: 1059-1078 - [c6]Allen Liu, Ankur Moitra:
Settling the robust learnability of mixtures of Gaussians. STOC 2021: 518-531 - [i13]Allen Liu, Ankur Moitra:
Learning GMMs with Nearly Optimal Robustness Guarantees. CoRR abs/2104.09665 (2021) - [i12]Allen Liu, Ankur Moitra:
How to Decompose a Tensor with Group Structure. CoRR abs/2106.02680 (2021) - [i11]Jerry Li, Allen Liu, Ankur Moitra:
Sparsification for Sums of Exponentials and its Algorithmic Applications. CoRR abs/2106.02774 (2021) - [i10]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. CoRR abs/2111.08057 (2021) - [i9]Jerry Li, Allen Liu:
Clustering Mixtures with Almost Optimal Separation in Polynomial Time. CoRR abs/2112.00706 (2021) - [i8]Allen Liu, Ankur Moitra:
Robust Voting Rules from Algorithmic Robust Statistics. CoRR abs/2112.06380 (2021) - 2020
- [j1]Zeev Dvir, Allen Liu:
Fourier and Circulant Matrices are Not Rigid. Theory Comput. 16: 1-48 (2020) - [c5]Allen Liu, Ankur Moitra:
Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation. COLT 2020: 2780-2829 - [c4]Allen Liu, Renato Paes Leme, Jon Schneider:
Myersonian Regression. NeurIPS 2020 - [c3]Allen Liu, Ankur Moitra:
Tensor Completion Made Practical. NeurIPS 2020 - [i7]Allen Liu, Renato Paes Leme, Jon Schneider:
Contextual Search for General Hypothesis Classes. CoRR abs/2003.01703 (2020) - [i6]Allen Liu, Renato Paes Leme, Martin Pal, Jon Schneider, Balasubramanian Sivan:
Competing Optimally Against An Imperfect Prophet. CoRR abs/2004.10163 (2020) - [i5]Allen Liu, Ankur Moitra:
Tensor Completion Made Practical. CoRR abs/2006.03134 (2020) - [i4]Allen Liu, Ankur Moitra:
Settling the Robust Learnability of Mixtures of Gaussians. CoRR abs/2011.03622 (2020)
2010 – 2019
- 2019
- [c2]Zeev Dvir, Allen Liu:
Fourier and Circulant Matrices Are Not Rigid. CCC 2019: 17:1-17:23 - [i3]Zeev Dvir, Allen Liu:
Fourier and Circulant Matrices are Not Rigid. CoRR abs/1902.07334 (2019) - [i2]Zeev Dvir, Allen Liu:
Fourier and Circulant Matrices are Not Rigid. Electron. Colloquium Comput. Complex. TR19 (2019) - 2018
- [c1]Allen Liu, Ankur Moitra:
Efficiently Learning Mixtures of Mallows Models. FOCS 2018: 627-638 - [i1]Allen Liu, Ankur Moitra:
Efficiently Learning Mixtures of Mallows Models. CoRR abs/1808.05731 (2018)
Coauthor Index
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last updated on 2024-12-10 21:48 CET by the dblp team
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