35 citations · 56 across the 6 of their papers we have counts for
7 papers
Terminal Dimension Reduction for Time Series with Applications
Alexander Munteanu, Matteo Russo, David Saulpic +1
Terminal embeddings have emerged as a powerful tool for dimension reduction. Given a set of points , a terminal embedding is a mapping $f:\mathbb{R}^d\righta…
Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivošija, Alexander Munteanu, André Nusser +1
This paper introduces -Dynamic Time Warping (-DTW), a novel dissimilarity measure for polygonal curves. -DTW has stronger metric properties than Dynamic Time Warping (DTW)…
Optimal Sketching Bounds for Sparse Linear Regression
Tung Mai, Alexander Munteanu, Cameron Musco +3
We study oblivious sketching for -sparse linear regression under various loss functions such as an norm, or from a broad class of hinge-like loss functions, which inclu…
An Empirical Evaluation of -Means Coresets
Chris Schwiegelshohn, Omar Ali Sheikh-Omar
Coresets are among the most popular paradigms for summarizing data. In particular, there exist many high performance coresets for clustering problems such as -means in both theo…
Maximizing Online Utilization with Commitment
Chris Schwiegelshohn, Uwe Schwiegelshohn
We investigate online scheduling with commitment for parallel identical machines. Our objective is to maximize the total processing time of accepted jobs. As soon as a job has been…
Fair Coresets and Streaming Algorithms for Fair k-Means Clustering
Melanie Schmidt, Chris Schwiegelshohn, Christian Sohler
We study fair clustering problems as proposed by Chierichetti et al. (NIPS 2017). Here, points have a sensitive attribute and all clusters in the solution are required to be balanc…