8 citations · 10 across the 6 of their papers we have counts for
6 papers
ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation
Yannis Karmim, Elias Ramzi, Raphaël Fournier-S'niehotta +1
Graph Neural Networks (GNNs), especially message-passing-based models, have become prominent in top-k recommendation tasks, outperforming matrix factorization models due to their a…
GalLoP: Learning Global and Local Prompts for Vision-Language Models
Marc Lafon, Elias Ramzi, Clément Rambour +2
Prompt learning has been widely adopted to efficiently adapt vision-language models (VLMs), e.g. CLIP, for few-shot image classification. Despite their success, most prompt learnin…
Optimization of Rank Losses for Image Retrieval
Elias Ramzi, Nicolas Audebert, Clément Rambour +3
In image retrieval, standard evaluation metrics rely on score ranking, \eg average precision (AP), recall at k (R@k), normalized discounted cumulative gain (NDCG). In this work we…
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
Marc Lafon, Elias Ramzi, Clément Rambour +1
Out-of-distribution (OOD) detection is a critical requirement for the deployment of deep neural networks. This paper introduces the HEAT model, a new post-hoc OOD detection method…
Hierarchical Average Precision Training for Pertinent Image Retrieval
Elias Ramzi, Nicolas Audebert, Nicolas Thome +2
Image Retrieval is commonly evaluated with Average Precision (AP) or Recall@k. Yet, those metrics, are limited to binary labels and do not take into account errors' severity. This…
Robust and Decomposable Average Precision for Image Retrieval
Elias Ramzi, Nicolas Thome, Clément Rambour +2
In image retrieval, standard evaluation metrics rely on score ranking, e.g. average precision (AP). In this paper, we introduce a method for robust and decomposable average precisi…