21 citations · 41 across the 5 of their papers we have counts for
6 papers
Predictive Flows for Faster Ford-Fulkerson
Sami Davies, Benjamin Moseley, Sergei Vassilvitskii +1
Recent work has shown that leveraging learned predictions can improve the running time of algorithms for bipartite matching and similar combinatorial problems. In this work, we bui…
An Objective for Hierarchical Clustering in Euclidean Space and its Connection to Bisecting K-means
Benjamin Moseley, Yuyan Wang
This paper explores hierarchical clustering in the case where pairs of points have dissimilarity scores (e.g. distances) as a part of the input. The recently introduced objective f…
Relational Algorithms for k-means Clustering
Benjamin Moseley, Kirk Pruhs, Alireza Samadian +1
This paper gives a k-means approximation algorithm that is efficient in the relational algorithms model. This is an algorithm that operates directly on a relational database withou…
Fair Hierarchical Clustering
Sara Ahmadian, Alessandro Epasto, Marina Knittel +6
As machine learning has become more prevalent, researchers have begun to recognize the necessity of ensuring machine learning systems are fair. Recently, there has been an interest…
Embracing the Blessing of Dimensionality in Factor Models
Quefeng Li, Guang Cheng, Jianqing Fan +1
Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covarianc…
Robust Estimation of High-Dimensional Mean Regression
Jianqing Fan, Quefeng Li, Yuyan Wang
Data subject to heavy-tailed errors are commonly encountered in various scientific fields, especially in the modern era with explosion of massive data. To address this problem, pro…