2 citations · 3 across the 9 of their papers we have counts for
9 papers
Approximation Preserving Coresets
Milind Prabhu, Chris Schwiegelshohn, Sudarshan Shyam
Clustering in a big data setting is an intensively studied problem, with coresets emerging as one of the important paradigms in this line of work. Given a cost function $\text{cost…
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi +1
We introduce the linear-transformation model, a distributed model of differentially private data analysis. Clients have access to a trusted platform capable of applying a public ma…
Simple and Optimal Sublinear Algorithms for Mean Estimation
Beatrice Bertolotti, Matteo Russo, Chris Schwiegelshohn +1
We study the sublinear multivariate mean estimation problem in -dimensional Euclidean space. Specifically, we aim to find the mean of a ground point set , which minimizes…
Low-Distortion Clustering with Ordinal and Limited Cardinal Information
Jakob Burkhardt, Ioannis Caragiannis, Karl Fehrs +3
Motivated by recent work in computational social choice, we extend the metric distortion framework to clustering problems. Given a set of agents located in an underlying metric…
Adaptive Out-Orientations with Applications
Chandra Chekuri, Aleksander Bjørn Christiansen, Jacob Holm +4
We give improved algorithms for maintaining edge-orientations of a fully-dynamic graph, such that the out-degree of each vertex is bounded. On one hand, we show how to orient the e…
On Generalization Bounds for Projective Clustering
Maria Sofia Bucarelli, Matilde Fjeldsø Larsen, Chris Schwiegelshohn +1
Given a set of points, clustering consists of finding a partition of a point set into clusters such that the center to which a point is assigned is as close as possible. Most c…
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lion Kamma, Kasper Green Larsen +2
The sparse Johnson-Lindenstrauss transform is one of the central techniques in dimensionality reduction. It supports embedding a set of points in into $m=O(\vare…
Optimally Interpolating between Ex-Ante Fairness and Welfare
Mikael Møller Høgsgaard, Panagiotis Karras, Wenyue Ma +2
For the fundamental problem of allocating a set of resources among individuals with varied preferences, the quality of an allocation relates to the degree of fairness and the colle…
Adaptive Out-Orientations with Applications
Aleksander B. G. Christiansen, Jacob Holm, Ivor van der Hoog +2
We give improved algorithms for maintaining edge-orientations of a fully-dynamic graph, such that the out-degree of each vertex is bounded. On one hand, we show how to orient the e…