159 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- École PolytechniqueFR3 papers
- Centre Inria de SaclayFR2 papers
- Institut Systèmes Intelligents et de RobotiqueFR2 papers
- Advanced Inhalation Therapies (Israel)IL1 paper
- Beth Israel Deaconess Medical CenterUS1 paper
- Centre BorelliFR1 paper
- Criteo (France)FR1 paper
- Harvard UniversityUS1 paper
- Immune Deficiency FoundationUS1 paper
- Institut de Biologie de l'École Normale SupérieureFR1 paper
- Institut national de recherche en sciences et technologies du numériqueFR1 paper
- Kantonsspital AarauCH1 paper
15 papers
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…
Estimating Learners' Skill Acquisition Without Temporal Information
Ryosuke Nagai, Kyohei Atarashi, Koh Takeuchi +2
Recent research in educational data mining, especially knowledge tracing, has focused on predicting learners' future knowledge states to support adaptive instruction. However, in m…
Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
Clémence Réda, Tomas Rigaux, Hiba Bederina +3
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also mi…
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…
On the calibration of survival models with competing risks
Julie Alberge, Tristan Haugomat, Gaël Varoquaux +1
Survival analysis deals with modeling the time until an event occurs, and accurate probability estimates are crucial for decision-making, particularly in the competing-risks settin…
A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents
Jean Vassoyan, Anan Schütt, Jill-Jênn Vie +3
Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to ad…
Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks
Julie Alberge, Vincent Maladière, Olivier Grisel +2
When dealing with right-censored data, where some outcomes are missing due to a limited observation period, survival analysis -- known as time-to-event analysis -- focuses on predi…
Imputation for prediction: beware of diminishing returns
Marine Le Morvan, Gaël Varoquaux
Missing values are prevalent across various fields, posing challenges for training and deploying predictive models. In this context, imputation is a common practice, driven by the…
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks
Julie Alberge, Vincent Maladière, Olivier Grisel +2
When data are right-censored, i.e. some outcomes are missing due to a limited period of observation, survival analysis can compute the "time to event". Multiple classes of outcomes…
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…
Vectorizing string entries for data processing on tables: when are larger language models better?
Léo Grinsztajn, Edouard Oyallon, Myung Jun Kim +1
There are increasingly efficient data processing pipelines that work on vectors of numbers, for instance most machine learning models, or vector databases for fast similarity searc…
Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model
Jill-Jênn Vie, Hisashi Kashima
Knowledge tracing consists in predicting the performance of some students on new questions given their performance on previous questions, and can be a prior step to optimizing asse…
Causal thinking for decision making on Electronic Health Records: why and how
Matthieu Doutreligne, Tristan Struja, Judith Abecassis +3
Accurate predictions, as with machine learning, may not suffice to provide optimal healthcare for every patient. Indeed, prediction can be driven by shortcuts in the data, such as…
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.…
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…