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Leveraging sparse and shared feature activations for disentangled representation learning
Marco Fumero · Florian Wenzel · Luca Zancato · Alessandro Achille · Emanuele Rodola · Stefano Soatto · Bernhard Schölkopf · Francesco Locatello
Event URL: https://openreview.net/forum?id=8NMwh7TVhw »

Recovering the latent factors of variation of high dimensional data has so far focused on simple synthetic settings. Mostly building on unsupervised and weakly-supervised objectives, prior work missed out on the positive implications for representation learning on real world data. In this work, we propose to leverage knowledge extracted from a diversified set of supervised tasks to learn a common disentangled representation. Assuming each supervised task only depends on an unknown subset of the factors of variation, we disentangle the feature space of a supervised multi-task model, with features activating sparsely across different tasks and information being shared as appropriate. Importantly, we never directly observe the factors of variations but establish that access to multiple tasks is sufficient for identifiability under sufficiency and minimality assumptions. We validate our approach on six real world distribution shift benchmarks, and different data modalities (images, text), demonstrating how disentangled representations can be transferred to real settings.

Author Information

Marco Fumero (La Sapienza, University of Rome)
Florian Wenzel (AWS)
Luca Zancato (University of Padova)
Alessandro Achille (California Institute of Technology)
Emanuele Rodola (Sapienza University of Rome)
Stefano Soatto (UCLA)
Bernhard Schölkopf (MPI for Intelligent Systems Tübingen, Germany)

Bernhard Scholkopf received degrees in mathematics (London) and physics (Tubingen), and a doctorate in computer science from the Technical University Berlin. He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). In 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in 2010 he founded the Max Planck Institute for Intelligent Systems. For further information, see www.kyb.tuebingen.mpg.de/~bs.

Francesco Locatello (Amazon Web Services)

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