3 citations · 8 across the 14 of their papers we have counts for
6 papers · 1 filter
Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond Moments
Trung Dang, Jasper C. H. Lee, Maoyuan Song +1
There is growing interest in improving our algorithmic understanding of fundamental statistical problems such as mean estimation, driven by the goal of understanding the limits of…
Two-Stage Predict+Optimize for Mixed Integer Linear Programs with Unknown Parameters in Constraints
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee
Consider the setting of constrained optimization, with some parameters unknown at solving time and requiring prediction from relevant features. Predict+Optimize is a recent framewo…
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate
Shivam Gupta, Jasper C. H. Lee, Eric Price
The mean of an unknown variance- distribution can be estimated from samples with variance and nearly corresponding subgaussian rate. When is known…
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +2
We study the problem of list-decodable Gaussian covariance estimation. Given a multiset of points in such that an unknown fraction of points in ar…
Branch & Learn with Post-hoc Correction for Predict+Optimize with Unknown Parameters in Constraints
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee
Combining machine learning and constrained optimization, Predict+Optimize tackles optimization problems containing parameters that are unknown at the time of solving. Prior works f…
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
Shivam Gupta, Jasper C. H. Lee, Eric Price
In location estimation, we are given samples from a known distribution shifted by an unknown translation , and want to estimate as precisely as possible. Asymptotica…