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Found 4 papers, 3 papers with code
Approximate Neural Architecture Search via Operation Distribution Learning
The standard paradigm in Neural Architecture Search (NAS) is to search for a fully deterministic architecture with specific operations and connections.
NAS evaluation is frustratingly hard
As such, and due to the under-use of ablation studies, there is a lack of clarity regarding why certain methods are more effective than others.
Domain Generalization by Solving Jigsaw Puzzles
Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but then the children fill in the gaps on their own.
Hallucinating Agnostic Images to Generalize Across Domains
The ability to generalize across visual domains is crucial for the robustness of artificial recognition systems.
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