![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Matthäus Kleindessner
Person information
Refine list
![note](https://dblp.uni-trier.de/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Journal Articles
- 2021
- [j2]Yiyi Huang, Matthäus Kleindessner, Alexey A. Munishkin, Debvrat Varshney, Pei Guo, Jianwu Wang
:
Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere. Frontiers Big Data 4: 642182 (2021) - 2017
- [j1]Matthäus Kleindessner, Ulrike von Luxburg:
Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis. J. Mach. Learn. Res. 18: 58:1-58:52 (2017)
Conference and Workshop Papers
- 2023
- [c20]Junaid Ali
, Matthäus Kleindessner
, Florian Wenzel
, Kailash Budhathoki
, Volkan Cevher
, Chris Russell
:
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. AIES 2023: 809-833 - [c19]Matthäus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar:
Efficient fair PCA for fair representation learning. AISTATS 2023: 5250-5270 - [c18]Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox:
Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. ICLR 2023 - [c17]Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell:
When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML 2023: 31969-31989 - 2022
- [c16]Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell:
Pairwise Fairness for Ordinal Regression. AISTATS 2022: 3381-3417 - [c15]Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
:
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CVPR 2022: 10400-10411 - [c14]Azin Ghazimatin, Matthäus Kleindessner, Chris Russell
, Ziawasch Abedjan, Jacek Golebiowski:
Measuring Fairness of Rankings under Noisy Sensitive Information. FAccT 2022: 2263-2279 - [c13]Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang:
Active Sampling for Min-Max Fairness. ICML 2022: 53-65 - [c12]Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian:
Individual Preference Stability for Clustering. ICML 2022: 197-246 - [c11]Paul Rolland, Volkan Cevher
, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello:
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. ICML 2022: 18741-18753 - [c10]Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell:
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. NeurIPS 2022 - 2021
- [c9]Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang:
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. FAccT 2021: 206-214 - [c8]Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler:
Backward-Compatible Prediction Updates: A Probabilistic Approach. NeurIPS 2021: 116-128 - 2020
- [c7]Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern:
Equalized odds postprocessing under imperfect group information. AISTATS 2020: 1770-1780 - 2019
- [c6]Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern:
Fair k-Center Clustering for Data Summarization. ICML 2019: 3448-3457 - [c5]Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern:
Guarantees for Spectral Clustering with Fairness Constraints. ICML 2019: 3458-3467 - 2018
- [c4]Matthäus Kleindessner, Pranjal Awasthi:
Crowdsourcing with Arbitrary Adversaries. ICML 2018: 2713-2722 - 2017
- [c3]Matthäus Kleindessner, Ulrike von Luxburg:
Kernel functions based on triplet comparisons. NIPS 2017: 6807-6817 - 2015
- [c2]Matthäus Kleindessner, Ulrike von Luxburg:
Dimensionality estimation without distances. AISTATS 2015 - 2014
- [c1]Matthäus Kleindessner, Ulrike von Luxburg:
Uniqueness of Ordinal Embedding. COLT 2014: 40-67
Informal and Other Publications
- 2024
- [i18]Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis:
Inference Optimization of Foundation Models on AI Accelerators. CoRR abs/2407.09111 (2024) - 2023
- [i17]Matthäus Kleindessner, Michele Donini, Chris Russell
, Muhammad Bilal Zafar:
Efficient fair PCA for fair representation learning. CoRR abs/2302.13319 (2023) - [i16]Junaid Ali, Matthäus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell:
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. CoRR abs/2310.11867 (2023) - 2022
- [i15]Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello:
Score matching enables causal discovery of nonlinear additive noise models. CoRR abs/2203.04413 (2022) - [i14]Dominik Zietlow, Michael Lohaus, Guha Balakrishnan
, Matthäus Kleindessner, Francesco Locatello
, Bernhard Schölkopf, Chris Russell:
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CoRR abs/2203.04913 (2022) - [i13]Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
:
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. CoRR abs/2204.04440 (2022) - [i12]Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian:
Individual Preference Stability for Clustering. CoRR abs/2207.03600 (2022) - [i11]Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox:
Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. CoRR abs/2207.05027 (2022) - 2021
- [i10]Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang:
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. CoRR abs/2102.08410 (2021) - [i9]Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell:
Pairwise Fairness for Ordinal Regression. CoRR abs/2105.03153 (2021) - [i8]Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler:
Backward-Compatible Prediction Updates: A Probabilistic Approach. CoRR abs/2107.01057 (2021) - 2020
- [i7]Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern:
A Notion of Individual Fairness for Clustering. CoRR abs/2006.04960 (2020) - [i6]Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie Zhang:
Adaptive Sampling to Reduce Disparate Performance. CoRR abs/2006.06879 (2020) - 2019
- [i5]Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern:
Fair k-Center Clustering for Data Summarization. CoRR abs/1901.08628 (2019) - [i4]Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern:
Guarantees for Spectral Clustering with Fairness Constraints. CoRR abs/1901.08668 (2019) - [i3]Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern:
Effectiveness of Equalized Odds for Fair Classification under Imperfect Group Information. CoRR abs/1906.03284 (2019) - 2016
- [i2]Matthäus Kleindessner, Ulrike von Luxburg:
Lens depth function and k-relative neighborhood graph: versatile tools for ordinal data analysis. CoRR abs/1602.07194 (2016) - [i1]Matthäus Kleindessner, Ulrike von Luxburg:
Kernel functions based on triplet similarity comparisons. CoRR abs/1607.08456 (2016)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-18 00:36 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint