Allen Liu

Allen Liu

I am currently a first-year graduate student in EECS at MIT working under the wonderful supervision of Ankur Moitra. I also completed my undergraduate degree (in mathematics) at MIT. I am generally interested in algorithms and learning theory, particularly developing algorithms for machine learning with provable guarantees. My work is supported by an NSF Graduate Research Fellowship and a Hertz Fellowship.

Email: cliu568 at mit dot edu

Publications

Learning GMMs with Nearly Optimal Robustness Guarantees
with Ankur Moitra
Manuscript

How to Decompose a Tensor with Group Structure
with Ankur Moitra
Manuscript

Sparsification for Sums of Exponentials and its Algorithmic Applications
with Jerry Li, Ankur Moitra
Manuscript

Variable Decomposition for Prophet Inequalities and Optimal Ordering
with Renato Paes Leme, Martin Pal, Jon Schneider, Balasubramanian Sivan
EC 2021

Settling the Robust Learnability of Mixtures of Gaussians
with Ankur Moitra
STOC 2021

Optimal Contextual Pricing and Extensions
with Renato Paes Leme, Jon Schneider
SODA 2021

Distributed Load Balancing: A New Framework and Improved Guarantees
with Sara Ahmadian, Binghui Peng, Morteza Zadimoghaddam
ITCS 2021

Tensor Completion Made Practical
with Ankur Moitra
NeurIPS 2020

Myersonian Regression
with Renato Paes Leme, Jon Schneider
NeurIPS 2020

Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation
with Ankur Moitra
COLT 2020

Fourier and Circulant Matrices are Not Rigid
with Zeev Dvir
Preliminary version appeared in CCC 2019
Full version in Theory of Computing 2020

Efficiently Learning Mixtures of Mallows Models
with Ankur Moitra
FOCS 2018

Wavelet Decomposition and Bandwidth of Functions Defined on Vector Spaces over Finite Fields
with Alex Iosevich, Azita Mayeli, Jonathan Pakianathan
Bulletin of the Hellenic Mathematical Society 2018