DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
In recommendation scenarios, there are two long-standing challenges, ie, selection bias and
data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through …
data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through …
[HTML][HTML] Application of machine learning models in social sciences: managing nonlinear relationships
T Kyriazos, M Poga - Encyclopedia, 2024 - mdpi.com
Definition The increasing complexity of social science data and phenomena necessitates
using advanced analytical techniques to capture nonlinear relationships that traditional …
using advanced analytical techniques to capture nonlinear relationships that traditional …
An adaptive framework for confidence-constraint rule set learning algorithm in large dataset
Decision rules have been successfully used in various classification applications because of
their interpretability and efficiency. In many real-world scenarios, especially in industrial …
their interpretability and efficiency. In many real-world scenarios, especially in industrial …
Explicabilité des modèles profonds et méthodologie pour son évaluation: application aux données textuelles de Pôle emploi
G Jouis - 2023 - theses.hal.science
L'intelligence Artificielle fait partie de notre quotidien. Les modèles développés sont de plus
en plus complexes. Les régulations telles que la Loi Pour une République Numérique …
en plus complexes. Les régulations telles que la Loi Pour une République Numérique …
Classification and Interpretation of ECG Arrhythmia through Deep Learning Techniques
A Shobanadevi, T Veeramakali - 2023 - researchsquare.com
Digitizing healthcare systems is highly essential to identify diseases at an early stage and
thus preventing any catastrophes regarding people's health. One such critical health issue …
thus preventing any catastrophes regarding people's health. One such critical health issue …