Michael Lohaus

4 papers · 2020–2023 · 4 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze ❓ The Questioner 📈 Trend Setter

Venues

CVPR (1) ICML (1) JMLR (1) NeurIPS (1)

Top co-authors

Ulrike Von Luxburg (2) Matthäus Kleindessner (2) Chris Russell (2) Francesco Locatello (2) Guha Balakrishnan (1) Michaël Perrot (1) Dominik Zietlow (1) Leena Chennuru Vankadara (1) Siavash Haghiri (1) Krishnaram Kenthapadi (1)

Research topics

Machine Learning (4) Application Areas (3) Artificial Intelligence (2) Deep Learning (2) Core AI (2) Core Methods (2) Learning Types · Deep Learning (2) Computer Vision (1) Analysis (1) Learning Types · Machine Learning (1)

Keywords

dimensionality reduction (1) metric learning (1) algorithmic fairness (1) non-convex optimization (1) computer vision (1) adaptive augmentation (1) constrained optimization (1) deep classifier (1) fairness constraint (1) local optima (1) constraint relaxation (1) demographic parity (1) bias-variance decomposition (1) triplet comparison (1) ordinal embedding (1) euclidean representation (1) neural network approach (1) fair classifier (1) protected attribute (1) neural network (1)

Papers

Insights into Ordinal Embedding Algorithms: A Systematic Evaluation JMLR 2023 Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks NeurIPS 2022 Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers CVPR 2022 Too Relaxed to Be Fair ICML 2020