Chris Schwiegelshohn
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
37
Venues
17
Active years
2009–2025
Best venue rank
A*
Where they publish
Papers
37 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | FOCS | Nearly Tight Regret Bounds for Profit Maximization in Bilateral Trade. | Simone Di Gregorio, Paul Dtting, Federico Fusco, Chris Schwiegelshohn |
| 2025 | ICML | Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. | Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten |
| 2025 | ICML | Distributed Differentially Private Data Analytics via Secure Sketching. | Jakob Burkhardt, Hannah Keller, Claudio Orlandi, Chris Schwiegelshohn |
| 2025 | ICML | Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves. | Amer Krivosija, Alexander Munteanu, Andr Nusser, Chris Schwiegelshohn |
| 2025 | SODA | A Tight VC-Dimension Analysis of Clustering Coresets with Applications. | Vincent Cohen-Addad, Andrew Draganov, Matteo Russo, David Saulpic, Chris Schwiegelshohn |
| 2025 | STOC | A (2+ε)-Approximation Algorithm for Metric k-Median. | Vincent Cohen-Addad, Fabrizio Grandoni, Euiwoong Lee, Chris Schwiegelshohn, Ola Svensson |
| 2025 | STOC | Almost Optimal PAC Learning for k-Means. | Vincent Cohen-Addad, Silvio Lattanzi, Chris Schwiegelshohn |
| 2024 | AAAI | Low-Distortion Clustering with Ordinal and Limited Cardinal Information. | Jakob Burkhardt, Ioannis Caragiannis, Karl Fehrs, Matteo Russo, Chris Schwiegelshohn, Sudarshan Shyam |
| 2024 | FOCS | Sensitivity Sampling for k-Means: Worst Case and Stability Optimal Coreset Bounds. | Nikhil Bansal, Vincent Cohen-Addad, Milind Prabhu, David Saulpic, Chris Schwiegelshohn |
| 2024 | ICML | Optimal Coresets for Low-Dimensional Geometric Median. | Peyman Afshani, Chris Schwiegelshohn |
| 2024 | ICML | Sparse Dimensionality Reduction Revisited. | Mikael Mller Hgsgaard, Lior Kamma, Kasper Green Larsen, Jelani Nelson, Chris Schwiegelshohn |
| 2024 | SODA | Adaptive Out-Orientations with Applications. | Chandra Chekuri, Aleksander Bjrn Grodt Christiansen, Jacob Holm, Ivor van der Hoog, Kent Quanrud, Eva Rotenberg, Chris Schwiegelshohn |
| 2023 | AISTATS | Optimal Sketching Bounds for Sparse Linear Regression. | Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff |
| 2023 | FOCS | Deterministic Clustering in High Dimensional Spaces: Sketches and Approximation. | Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn |
| 2023 | SODA | Breaching the 2 LMP Approximation Barrier for Facility Location with Applications to | Vincent Cohen-Addad, Fabrizio Grandoni, Euiwoong Lee, Chris Schwiegelshohn |
| 2022 | ESA | An Empirical Evaluation of k-Means Coresets. | Chris Schwiegelshohn, Omar Ali Sheikh-Omar |
| 2022 | FOCS | The Power of Uniform Sampling for Coresets. | Vladimir Braverman, Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Robert Krauthgamer, Chris Schwiegelshohn, Mads Bech Toftrup, Xuan Wu |
| 2022 | KDD | Scalable Differentially Private Clustering via Hierarchically Separated Trees. | Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii |
| 2022 | STOC | Towards optimal lower bounds for k-median and k-means coresets. | Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn |
| 2021 | STOC | A new coreset framework for clustering. | Vincent Cohen-Addad, David Saulpic, Chris Schwiegelshohn |
| 2020 | CIKM | Spectral Relaxations and Fair Densest Subgraphs. | Aris Anagnostopoulos, Luca Becchetti, Adriano Fazzone, Cristina Menghini, Chris Schwiegelshohn |
| 2020 | SPAA | Commitment and Slack for Online Load Maximization. | Samin Jamalabadi, Chris Schwiegelshohn, Uwe Schwiegelshohn |
| 2019 | GI | On Coresets for Logistic Regression. | Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David P. Woodruff |
| 2019 | WWW | Algorithms for Fair Team Formation in Online Labour Marketplaces✱. | Giorgio Barnab, Adriano Fazzone, Stefano Leonardi, Chris Schwiegelshohn |
| 2019 | SODA | (1 + ε)-Approximate Incremental Matching in Constant Deterministic Amortized Time. | Fabrizio Grandoni, Stefano Leonardi, Piotr Sankowski, Chris Schwiegelshohn, Shay Solomon |
| 2019 | STOC | Oblivious dimension reduction for | Luca Becchetti, Marc Bury, Vincent Cohen-Addad, Fabrizio Grandoni, Chris Schwiegelshohn |
| 2019 | WAOA | Fair Coresets and Streaming Algorithms for Fair k-means. | Melanie Schmidt, Chris Schwiegelshohn, Christian Sohler |
| 2018 | CIKM | Random Projection to Preserve Patient Privacy. | Aris Anagnostopoulos, Fabio Angeletti, Federico Arcangeli, Chris Schwiegelshohn, Andrea Vitaletti |
| 2018 | WSDM | Sketch 'Em All: Fast Approximate Similarity Search for Dynamic Data Streams. | Marc Bury, Chris Schwiegelshohn, Mara Sorella |
| 2017 | FOCS | On the Local Structure of Stable Clustering Instances. | Vincent Cohen-Addad, Chris Schwiegelshohn |
| 2017 | ICALP | On Finding the Jaccard Center. | Marc Bury, Chris Schwiegelshohn |
| 2016 | ESA | The Power of Migration for Online Slack Scheduling. | Chris Schwiegelshohn, Uwe Schwiegelshohn |
| 2016 | ICALP | Diameter and k-Center in Sliding Windows. | Vincent Cohen-Addad, Chris Schwiegelshohn, Christian Sohler |
| 2015 | ESA | Sublinear Estimation of Weighted Matchings in Dynamic Data Streams. | Marc Bury, Chris Schwiegelshohn |
| 2013 | ESA | BICO: BIRCH Meets Coresets for k-Means Clustering. | Hendrik Fichtenberger, Marc Gill, Melanie Schmidt, Chris Schwiegelshohn, Christian Sohler |
| 2012 | ALENEX | Solving the Minimum String Cover Problem. | Stefan Canzar, Tobias Marschall, Sven Rahmann, Chris Schwiegelshohn |
| 2009 | GECCO | PEPPA: a project for evolutionary predator prey algorithms. | Hendrik Blom, Christiane Kch, Katja Losemann, Chris Schwiegelshohn |