output
20222026
most citedWhy do tree-based models still outperform deep learning on tabular data?

159 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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5 papers · 1 filter

cs.LG2026

Counterfactual learning of new adaptive instructional policies using logged data

Samuel Girard, Sein Minn, Amel Bouzeghoub +1

Optimizing instructional policies in Intelligent Tutoring Systems (ITS) typically requires costly online experimentation or student simulators that may fail to capture real-world d…

cs.LG2026

Live Knowledge Tracing: Real-Time Adaptation using Tabular Foundation Models

Mounir Lbath, Alexandre Parésy, Abdelkayoum Kaddouri +2

Deep knowledge tracing models have achieved significant breakthroughs in modeling student learning trajectories. However, these architectures require substantial training time and…

cs.LG2024

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits

Julien Zhou, Pierre Gaillard, Thibaud Rahier +2

We address the problem of stochastic combinatorial semi-bandits, where a player selects among P actions from the power set of a set containing d base items. Adaptivity to the probl…

cs.LG2022★ 5 cited

Beyond calibration: estimating the grouping loss of modern neural networks

Alexandre Perez-Lebel, Marine Le Morvan, Gaël Varoquaux

The ability to ensure that a classifier gives reliable confidence scores is essential to ensure informed decision-making. To this end, recent work has focused on miscalibration, i.…

cs.LG2022★ 159 cited

Why do tree-based models still outperform deep learning on tabular data?

Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux

While deep learning has enabled tremendous progress on text and image datasets, its superiority on tabular data is not clear. We contribute extensive benchmarks of standard and nov…