Victor Quétu

According to our database, Victor Quétu authored at least 11 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Memory-Optimized Once-For-All Network.

Maxime Girard, Victor Quétu, Samuel Tardieu, Van-Tam Nguyen, Enzo Tartaglione

CoRR, 2024

LaCoOT: Layer Collapse through Optimal Transport.

Victor Quétu, Nour Hezbri, Enzo Tartaglione

CoRR, 2024

NEPENTHE: Entropy-Based Pruning as a Neural Network Depth's Reducer.

Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione

CoRR, 2024

The Simpler The Better: An Entropy-Based Importance Metric to Reduce Neural Networks' Depth.

Victor Quétu, Zhu Liao, Enzo Tartaglione

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?

Victor Quétu, Enzo Tartaglione

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Disentangling private classes through regularization.

Enzo Tartaglione, Francesca Gennari, Victor Quétu, Marco Grangetto

Neurocomputing, October, 2023

The Quest of Finding the Antidote to Sparse Double Descent.

Victor Quétu, Marta Milovanovic

CoRR, 2023

Dodging the Sparse Double Descent.

Victor Quétu, Enzo Tartaglione

CoRR, 2023

Dodging the Double Descent in Deep Neural Networks.

Victor Quétu, Enzo Tartaglione

Proceedings of the IEEE International Conference on Image Processing, 2023

Sparse Double Descent in Vision Transformers: Real or Phantom Threat?

Victor Quétu, Marta Milovanovic, Enzo Tartaglione

Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?

Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023