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- Centre National de la Recherche ScientifiqueFR443 papers
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82 papers · 1 filter
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare
Eran Tal
Bias in applications of machine learning (ML) to healthcare is usually attributed to unrepresentative or incomplete data, or to underlying health disparities. This article identifi…
Worrisome Properties of Neural Network Controllers and Their Symbolic Representations
Jacek Cyranka, Kevin E M Church, Jean-Philippe Lessard
We raise concerns about controllers' robustness in simple reinforcement learning benchmark problems. We focus on neural network controllers and their low neuron and symbolic abstra…
FAENet: Frame Averaging Equivariant GNN for Materials Modeling
Alexandre Duval, Victor Schmidt, Alex Hernandez Garcia +4
Applications of machine learning techniques for materials modeling typically involve functions known to be equivariant or invariant to specific symmetries. While graph neural netwo…
Improved knowledge distillation by utilizing backward pass knowledge in neural networks
Aref Jafari, Mehdi Rezagholizadeh, Ali Ghodsi
Knowledge distillation (KD) is one of the prominent techniques for model compression. In this method, the knowledge of a large network (teacher) is distilled into a model (student)…
Benchmarking missing-values approaches for predictive models on health databases
Alexandre Perez-Lebel, Gaël Varoquaux, Marine Le Morvan +2
BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values: incomplete observations. These large databa…
Flexible Option Learning
Martin Klissarov, Doina Precup
Temporal abstraction in reinforcement learning (RL), offers the promise of improving generalization and knowledge transfer in complex environments, by propagating information more…