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Pau Rodríguez López

2 accepted papers

2020

Synbols: Probing Learning Algorithms with Synthetic Datasets

NeurIPS 2020poster

Progress in the field of machine learning has been fueled by the introduction of benchmark datasets pushing the limits of existing algorithms. Enabling the design of datasets to test specific properties and failure modes of learning algorithms is thus a problem of high interest, as it has a direct…

2018

TADAM: Task dependent adaptive metric for improved few-shot learning

NeurIPS 2018poster

Few-shot learning has become essential for producing models that generalize from few examples. In this work, we identify that metric scaling and metric task conditioning are important to improve the performance of few-shot algorithms. Our analysis reveals that simple metric scaling completely change…

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