activity
20192024
most citedComparison of Neuronal Attention Models

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

LossVal: Efficient Data Valuation for Neural Networks

Tim Wibiral, Mohamed Karim Belaid, Maximilian Rabus +1

Assessing the importance of individual training samples is a key challenge in machine learning. Traditional approaches retrain models with and without specific samples, which is co…

cs.LG20241 cited

Pairwise Difference Learning for Classification

Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier

Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping from instances to outcomes in the sta…

cs.LG2023

Optimizing Data Shapley Interaction Calculation from O(2^n) to O(t n^2) for KNN models

Mohamed Karim Belaid, Dorra El Mekki, Maximilian Rabus +1

With the rapid growth of data availability and usage, quantifying the added value of each training data point has become a crucial process in the field of artificial intelligence.…

cs.CV2020

After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph Generation

Mohamed Karim Belaid

From object segmentation to word vector representations, Scene Graph Generation (SGG) became a complex task built upon numerous research results. In this paper, we focus on the las…

cs.LG20191 cited

Comparison of Neuronal Attention Models

Mohamed Karim Belaid

Recent models for image processing are using the Convolutional neural network (CNN) which requires a pixel per pixel analysis of the input image. This method works well. However, i…