Matthäus Kleindessner
16 papers · 2014–2023 · 6 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (24) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Trend Setter
🗃️
Keyword Collector
(78)
🌈
Renaissance Researcher
(5)
🔥
Unstoppable · Bronze
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The Questioner
(2)
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(16)
Core Methods
(12)
Application Areas
(9)
Artificial Intelligence
(6)
Core AI
(5)
Mathematics & Optimization
(4)
Mathematics
(4)
Deep Learning
(2)
Learning Types · Deep Learning
(2)
Learning Types · Machine Learning
(2)
Optimization & Theory
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Knowledge & Reasoning
(1)
Analysis
(1)
Keywords
group fairness
(3)
algorithmic fairness
(3)
dimensionality reduction
(2)
kernel methods
(2)
fairness constraint
(2)
nearest neighbor graph
(2)
metric learning
(2)
protected attribute
(2)
spectral clustering
(1)
causal discovery
(1)
binary classification
(1)
embedding learning
(1)
adaptive augmentation
(1)
fair classification
(1)
computer vision
(1)
intrinsic dimension
(1)
principal component analysis
(1)
kernel pca
(1)
outlier detection
(1)
game theory
(1)
Papers
Efficient fair PCA for fair representation learning
AISTATS 2023
When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
ICML 2023
Active Sampling for Min-Max Fairness
ICML 2022
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks
NeurIPS 2022
Individual Preference Stability for Clustering
ICML 2022
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers
CVPR 2022
Pairwise Fairness for Ordinal Regression
AISTATS 2022
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models
ICML 2022
Backward-Compatible Prediction Updates: A Probabilistic Approach
NeurIPS 2021
Equalized odds postprocessing under imperfect group information
AISTATS 2020
Fair k-Center Clustering for Data Summarization
ICML 2019
Guarantees for Spectral Clustering with Fairness Constraints
ICML 2019
Kernel functions based on triplet comparisons
NeurIPS 2017
Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis
JMLR 2017
Dimensionality estimation without distances
AISTATS 2015
Uniqueness of Ordinal Embedding
COLT 2014