Guillermo Ortiz-Jiménez

According to our database, Guillermo Ortiz-Jiménez authored at least 21 papers between 2018 and 2024.

Collaborative distances:

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

2024

LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging.

Ke Wang, Nikolaos Dimitriadis, Alessandro Favero, Guillermo Ortiz-Jiménez, François Fleuret, Pascal Frossard

CoRR, 2024

UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI.

Ilia Shumailov, Jamie Hayes, Eleni Triantafillou, Guillermo Ortiz-Jiménez, Nicolas Papernot, Matthew Jagielski, Itay Yona, Heidi Howard, Eugene Bagdasaryan

CoRR, 2024

Pi-DUAL: Using privileged information to distinguish clean from noisy labels.

Ke Wang, Guillermo Ortiz-Jiménez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Localizing Task Information for Improved Model Merging and Compression.

Ke Wang, Nikolaos Dimitriadis, Guillermo Ortiz-Jiménez, François Fleuret, Pascal Frossard

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Catastrophic overfitting can be induced with discriminative non-robust features.

Guillermo Ortiz-Jiménez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Grégory Rogez, Philip Torr

Trans. Mach. Learn. Res., 2023

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models.

Guillermo Ortiz-Jiménez, Alessandro Favero, Pascal Frossard

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

When does Privileged information Explain Away Label Noise?

Guillermo Ortiz-Jiménez, Mark Collier, Anant Nawalgaria, Alexander Nicholas D'Amour, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

Proceedings of the International Conference on Machine Learning, 2023

2022

Catastrophic overfitting is a bug but also a feature.

Guillermo Ortiz-Jiménez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Grégory Rogez, Philip H. S. Torr

CoRR, 2022

On the benefits of knowledge distillation for adversarial robustness.

Javier Maroto, Guillermo Ortiz-Jiménez, Pascal Frossard

CoRR, 2022

PRIME: A Few Primitives Can Boost Robustness to Common Corruptions.

Apostolos Modas, Rahul Rade, Guillermo Ortiz-Jiménez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

Proceedings of the Computer Vision - ECCV 2022, 2022

A Structured Dictionary Perspective on Implicit Neural Representations.

Gizem Yüce, Guillermo Ortiz-Jiménez, Beril Besbinar, Pascal Frossard

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Optimism in the Face of Adversity: Understanding and Improving Deep Learning Through Adversarial Robustness.

Guillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

Proc. IEEE, 2021

A neural anisotropic view of underspecification in deep learning.

Guillermo Ortiz-Jiménez, Itamar Franco Salazar-Reque, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

CoRR, 2021

What can linearized neural networks actually say about generalization?

Guillermo Ortiz-Jiménez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

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

2020

Neural Anisotropy Directions.

Guillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hold me tight! Influence of discriminative features on deep network boundaries.

Guillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On The Choice of Graph Neural Network Architectures.

Clément Vignac, Guillermo Ortiz-Jiménez, Pascal Frossard

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Forward-Backward Splitting for Optimal Transport Based Problems.

Guillermo Ortiz-Jiménez, Mireille El Gheche, Effrosyni Simou, Hermina Petric Maretic, Pascal Frossard

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Sparse Sampling for Inverse Problems With Tensors.

Guillermo Ortiz-Jiménez, Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus

IEEE Trans. Signal Process., 2019

CDOT: Continuous Domain Adaptation using Optimal Transport.

Guillermo Ortiz-Jiménez, Mireille El Gheche, Effrosyni Simou, Hermina Petric Maretic, Pascal Frossard

CoRR, 2019

2018

Sampling and Reconstruction of Signals on Product Graphs.

Guillermo Ortiz-Jiménez, Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018