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Sebastian Bordt
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2020 – today
- 2024
- [i12]Sebastian Bordt, Ulrike von Luxburg:
Statistics without Interpretation: A Sober Look at Explainable Machine Learning. CoRR abs/2402.02870 (2024) - [i11]Sebastian Bordt, Benjamin J. Lengerich, Harsha Nori, Rich Caruana:
Data Science with LLMs and Interpretable Models. CoRR abs/2402.14474 (2024) - [i10]Sebastian Bordt, Harsha Nori, Rich Caruana:
Elephants Never Forget: Testing Language Models for Memorization of Tabular Data. CoRR abs/2403.06644 (2024) - [i9]Sebastian Bordt, Harsha Nori, Vanessa Rodrigues, Besmira Nushi, Rich Caruana:
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models. CoRR abs/2404.06209 (2024) - 2023
- [b1]Sebastian Bordt:
Explainable Machine Learning and its Limitations. University of Tübingen, Germany, 2023 - [c6]Sebastian Bordt, Ulrike von Luxburg:
From Shapley Values to Generalized Additive Models and back. AISTATS 2023: 709-745 - [c5]Sebastian Bordt, Uddeshya Upadhyay, Zeynep Akata, Ulrike von Luxburg:
The Manifold Hypothesis for Gradient-Based Explanations. CVPR Workshops 2023: 3697-3702 - [c4]Suraj Srinivas, Sebastian Bordt, Himabindu Lakkaraju:
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness. NeurIPS 2023 - [i8]Sebastian Bordt, Ulrike von Luxburg:
ChatGPT Participates in a Computer Science Exam. CoRR abs/2303.09461 (2023) - [i7]Suraj Srinivas, Sebastian Bordt, Hima Lakkaraju:
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness. CoRR abs/2305.19101 (2023) - [i6]Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana:
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs. CoRR abs/2308.01157 (2023) - 2022
- [c3]Sebastian Bordt, Ulrike von Luxburg:
A Bandit Model for Human-Machine Decision Making with Private Information and Opacity. AISTATS 2022: 7300-7319 - [c2]Sebastian Bordt, Michèle Finck, Eric Raidl
, Ulrike von Luxburg:
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts. FAccT 2022: 891-905 - [i5]Sebastian Bordt, Michèle Finck, Eric Raidl, Ulrike von Luxburg:
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts. CoRR abs/2201.10295 (2022) - [i4]Sebastian Bordt, Uddeshya Upadhyay, Zeynep Akata, Ulrike von Luxburg:
The Manifold Hypothesis for Gradient-Based Explanations. CoRR abs/2206.07387 (2022) - [i3]Sebastian Bordt, Ulrike von Luxburg:
From Shapley Values to Generalized Additive Models and back. CoRR abs/2209.04012 (2022) - 2021
- [c1]Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar:
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models. AISTATS 2021: 3817-3825 - [i2]Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar:
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models. CoRR abs/2110.09476 (2021) - 2020
- [i1]Sebastian Bordt, Ulrike von Luxburg:
When Humans and Machines Make Joint Decisions: A Non-Symmetric Bandit Model. CoRR abs/2007.04800 (2020)
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