Claudio Mayrink Verdun

According to our database, Claudio Mayrink Verdun authored at least 26 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

ProofCompass: Enhancing Specialized Provers with LLM Guidance.

Nicolas Wischermann, Claudio Mayrink Verdun, Gabriel Poesia, Francesco Noseda

CoRR, July, 2025

Inference-Time Reward Hacking in Large Language Models.

Hadi Khalaf, Claudio Mayrink Verdun, Alex Oesterling, Himabindu Lakkaraju, Flávio du Pin Calmon

CoRR, June, 2025

HeavyWater and SimplexWater: Watermarking Low-Entropy Text Distributions.

Dor Tsur, Carol Xuan Long, Claudio Mayrink Verdun, Hsiang Hsu, Chen-Fu Chen, Haim H. Permuter, Sajani Vithana, Flávio P. Calmon

CoRR, June, 2025

Multi-Group Proportional Representation for Text-to-Image Models.

Sangwon Jung, Alex Oesterling, Claudio Mayrink Verdun, Sajani Vithana, Taesup Moon, Flávio P. Calmon

CoRR, May, 2025

GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection.

Mariia Seleznova, Hung-Hsu Chou, Claudio Mayrink Verdun, Gitta Kutyniok

CoRR, May, 2025

Optimized Couplings for Watermarking Large Language Models.

Dor Tsur, Carol Xuan Long, Claudio Mayrink Verdun, Hsiang Hsu, Haim H. Permuter, Flávio P. Calmon

CoRR, May, 2025

Soft Best-of-n Sampling for Model Alignment.

Claudio Mayrink Verdun, Alex Oesterling, Himabindu Lakkaraju, Flávio P. Calmon

CoRR, May, 2025

AI Alignment at Your Discretion.

Maarten Buyl, Hadi Khalaf, Claudio Mayrink Verdun, Lucas Monteiro Paes, Caio Cesar Vieira Machado, Flávio du Pin Calmon

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

Multi-Group Proportional Representations for Text-to-Image Models.

Sangwon Jung, Alex Oesterling, Claudio Mayrink Verdun, Sajani Vithana, Taesup Moon, Flávio P. Calmon

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Get rid of your constraints and reparametrize: A study in NNLS and implicit bias.

Hung-Hsu Chou, Johannes Maly, Claudio Mayrink Verdun, Bernardo Freitas Paulo da Costa, Heudson Mirandola

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

With or Without Replacement? Improving Confidence in Fourier Imaging.

Frederik Hoppe, Claudio Mayrink Verdun, Felix Krahmer, Marion I. Menzel, Holger Rauhut

CoRR, 2024

Multi-Group Proportional Representation.

Alex Oesterling, Claudio Mayrink Verdun, Carol Xuan Long, Alexander Glynn, Lucas Monteiro Paes, Sajani Vithana, Martina Cardone, Flávio P. Calmon

CoRR, 2024

Multi-Group Proportional Representation in Retrieval.

Alex Oesterling, Claudio Mayrink Verdun, Alexander Glynn, Carol Xuan Long, Lucas Monteiro Paes, Sajani Vithana, Martina Cardone, Flávio P. Calmon

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models.

Adam Karvonen, Benjamin Wright, Can Rager, Rico Angell, Jannik Brinkmann, Logan Smith, Claudio Mayrink Verdun, David Bau, Samuel Marks

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning.

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Imaging with Confidence: Uncertainty Quantification for High-Dimensional Undersampled MR Images.

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Sebastian Endt, Marion I. Menzel, Felix Krahmer, Holger Rauhut

Proceedings of the Computer Vision - ECCV 2024, 2024

Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence.

Claudio Mayrink Verdun, Oleh Melnyk, Felix Krahmer, Peter Jung

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Uncertainty Quantification For Learned ISTA.

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

High-Dimensional Confidence Regions in Sparse MRI.

Frederik Hoppe, Felix Krahmer, Claudio Mayrink Verdun, Marion I. Menzel, Holger Rauhut

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Uncertainty quantification for sparse Fourier recovery.

Frederik Hoppe, Felix Krahmer, Claudio Mayrink Verdun, Marion I. Menzel, Holger Rauhut

CoRR, 2022

Non-negative Least Squares via Overparametrization.

Hung-Hsu Chou, Johannes Maly, Claudio Mayrink Verdun

CoRR, 2022

2021

Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate.

Christian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples.

Christian Kümmerle, Claudio Mayrink Verdun

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Iteratively Reweighted Least Squares for 𝓁₁-minimization with Global Linear Convergence Rate.

Christian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger

CoRR, 2020

Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method.

Christian Kümmerle, Claudio Mayrink Verdun

CoRR, 2020

2018

Denoising and Completion of Structured Low-Rank Matrices via Iteratively Reweighted Least Squares.

Christian Kümmerle, Claudio Mayrink Verdun

CoRR, 2018