Nikolaos Dimitriadis

According to our database, Nikolaos Dimitriadis authored at least 14 papers between 2020 and 2026.

Collaborative distances:

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

2026

Model soups need only one ingredient.

Alireza Abdollahpoorrostam, Nikolaos Dimitriadis, Adam Hazimeh, Pascal Frossard

CoRR, February, 2026

2025

Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning.

Juan Garcia Giraldo, Nikolaos Dimitriadis, Ke Wang, Pascal Frossard

CoRR, April, 2025

MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs.

Ke Wang, Yiming Qin, Nikolaos Dimitriadis, Alessandro Favero, Pascal Frossard

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

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

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences.

Nikolaos Dimitriadis, Pascal Frossard, François Fleuret

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence.

Kyle Matoba, Nikolaos Dimitriadis, François Fleuret

Trans. Mach. Learn. Res., 2023

Flexible Channel Dimensions for Differentiable Architecture Search.

Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard

CoRR, 2023

SequeL: A Continual Learning Library in PyTorch and JAX.

Nikolaos Dimitriadis, François Fleuret, Pascal Frossard

CoRR, 2023

Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models.

Nikolaos Dimitriadis, Pascal Frossard, François Fleuret

Proceedings of the International Conference on Machine Learning, 2023

2022

The Theoretical Expressiveness of Maxpooling.

Kyle Matoba, Nikolaos Dimitriadis, François Fleuret

CoRR, 2022

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search.

Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Advances in Morphological Neural Networks: Training, Pruning and Enforcing Shape Constraints.

Nikolaos Dimitriadis, Petros Maragos

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Advances in the training, pruning and enforcement of shape constraints of Morphological Neural Networks using Tropical Algebra.

Nikolaos Dimitriadis, Petros Maragos

CoRR, 2020