3 citations · 8 across the 14 of their papers we have counts for
16 papers
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…
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +1
We study the fundamental task of outlier-robust mean estimation for heavy-tailed distributions in the presence of sparsity. Specifically, given a small number of corrupted samples…
Predict+Optimize for Packing and Covering LPs with Unknown Parameters in Constraints
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee
Predict+Optimize is a recently proposed framework which combines machine learning and constrained optimization, tackling optimization problems that contain parameters that are unkn…
Finite-Sample Maximum Likelihood Estimation of Location
Shivam Gupta, Jasper C. H. Lee, Eric Price +1
We consider 1-dimensional location estimation, where we estimate a parameter from samples , with each drawn i.i.d. from a known distribution . For fixed $f…
Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize
Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee +1
This paper proposes Branch & Learn, a framework for Predict+Optimize to tackle optimization problems containing parameters that are unknown at the time of solving. Given an optimiz…
Optimal Sub-Gaussian Mean Estimation in
Jasper C. H. Lee, Paul Valiant
We revisit the problem of estimating the mean of a real-valued distribution, presenting a novel estimator with sub-Gaussian convergence: intuitively, "our estimator, on any distrib…
Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
Uthsav Chitra, Kimberly Ding, Jasper C. H. Lee +1
Anomaly estimation, or the problem of finding a subset of a dataset that differs from the rest of the dataset, is a classic problem in machine learning and data mining. In both the…
Finding the Mode of a Kernel Density Estimate
Jasper C. H. Lee, Jerry Li, Christopher Musco +2
Given points in , how do we find a point which maximizes ? In other words, how do we find the maxim…
Uncertainty about Uncertainty: Optimal Adaptive Algorithms for Estimating Mixtures of Unknown Coins
Jasper C. H. Lee, Paul Valiant
Given a mixture between two populations of coins, "positive" coins that each have -- unknown and potentially different -- bias and "negative" coins with bias $\…
Augmenting Stream Constraint Programming with Eventuality Conditions
Jasper C. H. Lee, Jimmy H. M. Lee, Allen Z. Zhong
Stream constraint programming is a recent addition to the family of constraint programming frameworks, where variable domains are sets of infinite streams over finite alphabets. Pr…
Optimizing Star-Convex Functions
Jasper C. H. Lee, Paul Valiant
We introduce a polynomial time algorithm for optimizing the class of star-convex functions, under no restrictions except boundedness on a region about the origin, and Lebesgue meas…