Matthus Kleindessner
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
16
Venues
7
Active years
2014–2024
Best venue rank
A*
Where they publish
Papers
16 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | KDD | Inference Optimization of Foundation Models on AI Accelerators. | Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kbler, Jiaji Huang, Matthus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis |
| 2023 | AIES | Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. | Junaid Ali, Matthus Kleindessner, Florian Wenzel, Kailash Budhathoki, Volkan Cevher, Chris Russell |
| 2023 | AISTATS | Efficient fair PCA for fair representation learning. | Matthus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar |
| 2023 | ICLR | Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. | Andrii Zadaianchuk, Matthus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox |
| 2023 | ICML | When do Minimax-fair Learning and Empirical Risk Minimization Coincide? | Harvineet Singh, Matthus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell |
| 2022 | AISTATS | Pairwise Fairness for Ordinal Regression. | Matthus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell |
| 2022 | CVPR | Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. | Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthus Kleindessner, Francesco Locatello, Bernhard Schlkopf, Chris Russell |
| 2022 | ICML | Active Sampling for Min-Max Fairness. | Jacob D. Abernethy, Pranjal Awasthi, Matthus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang |
| 2022 | ICML | Individual Preference Stability for Clustering. | Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian |
| 2022 | ICML | Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. | Paul Rolland, Volkan Cevher, Matthus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schlkopf, Francesco Locatello |
| 2020 | AISTATS | Equalized odds postprocessing under imperfect group information. | Pranjal Awasthi, Matthus Kleindessner, Jamie Morgenstern |
| 2019 | ICML | Fair k-Center Clustering for Data Summarization. | Matthus Kleindessner, Pranjal Awasthi, Jamie Morgenstern |
| 2019 | ICML | Guarantees for Spectral Clustering with Fairness Constraints. | Matthus Kleindessner, Samira Samadi, Pranjal Awasthi, Jamie Morgenstern |
| 2018 | ICML | Crowdsourcing with Arbitrary Adversaries. | Matthus Kleindessner, Pranjal Awasthi |
| 2015 | AISTATS | Dimensionality estimation without distances. | Matthus Kleindessner, Ulrike von Luxburg |
| 2014 | COLT | Uniqueness of Ordinal Embedding. | Matthus Kleindessner, Ulrike von Luxburg |