Showing 2024Show all
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stat.ML2024
Learning Differentiable Surrogate Losses for Structured Prediction
Junjie Yang, Matthieu Labeau, Florence d'Alché-Buc
Structured prediction involves learning to predict complex structures rather than simple scalar values. The main challenge arises from the non-Euclidean nature of the output space,…
cs.CL2024
Revisiting Hierarchical Text Classification: Inference and Metrics
Roman Plaud, Matthieu Labeau, Antoine Saillenfest +1
Hierarchical text classification (HTC) is the task of assigning labels to a text within a structured space organized as a hierarchy. Recent works treat HTC as a conventional multil…
cs.LG2024
Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss
Paul Krzakala, Junjie Yang, Rémi Flamary +3
We propose Any2graph, a generic framework for end-to-end Supervised Graph Prediction (SGP) i.e. a deep learning model that predicts an entire graph for any kind of input. The frame…