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Abdoulaye Sakho

3 papers hereh-index 218 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • math.ST1
  • stat.ML1

identity via Semantic Scholar / OpenAlex

works on
fairness in AI 1gradient boosting 1in-processing methods 1optimal transport 1tabular data 1

From the 1 of 3 linked papers with an AI index.

most citedDo we need rebalancing strategies? A theoretical and empirical study around SMOTE and its variants

4 citations · 4 across the 2 of their papers we have counts for

collaborators

3 papers

math.ST2026

OT-FairBoost: Optimal Transport-Guided Gradient Boosting for Fairness Regularization on Tabular Data

Veronika Shilova, Abdoulaye Sakho, Younes Boumoussou +3

The paper proposes OT-FairBoost, an in-processing method that adds a Wasserstein-2 distance penalty to gradient-boosted tree training to improve group fairness while maintaining ac…

stat.ML2026★ 4 cited

Do we need rebalancing strategies? A theoretical and empirical study around SMOTE and its variants

Abdoulaye Sakho, Emmanuel Malherbe, Erwan Scornet

Synthetic Minority Oversampling Technique (SMOTE) is a common rebalancing strategy for handling imbalanced tabular data sets. However, few works analyze SMOTE theoretically. In thi…

cs.LG2025

Harnessing Mixed Features for Imbalance Data Oversampling: Application to Bank Customers Scoring

Abdoulaye Sakho, Emmanuel Malherbe, Carl-Erik Gauthier +1

This study investigates rare event detection on tabular data within binary classification. Standard techniques to handle class imbalance include SMOTE, which generates synthetic sa…

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