Jul 12, 2023 · Few-shot learning datasets contain a large number of classes with only a few examples in each. Existing datasets may contain thousands of ...

This work assembles a new dataset with each class containing a small subset from each of the 1000 classes of ImageNet-1k, and uses an evolutionary approach ...

We focus on the effectiveness of error with image generation implying suggestibility and hypothesize that errors encourage the students to memorize the ...

OmnImage CI. The OmniImage dataset contains a 1000 classes with 20|100 images each, downsized to 84x84 pixels.

Meyer-Lee, & Cheney, N. AutoML Conference Workshop, 2023. Omnimage: Evolving 1k image cliques for few-shot learning. Frati, L., Traft, N., & Cheney, N ...

Learning to continually learn. S Beaulieu, L Frati, T Miconi, J Lehman ... OmnImage: Evolving 1k Image Cliques for Few-Shot Learning. L Frati, N Traft ...

OmnImage: Evolving 1k Image Cliques for Few-Shot Learning · Author Picture Lapo Frati. University of Vermont, Burlington, United States of America.

Coping with seasons: evolutionary dynamics of gene networks in a changing environment · OmnImage: Evolving 1k Image Cliques for Few-Shot Learning.

Co-authors ; OmnImage: Evolving 1k Image Cliques for Few-Shot Learning. L Frati, N Traft, N Cheney. Proceedings of the Genetic and Evolutionary Computation ...

Lapo Frati, Neil Traft "OmnImage: Evolving 1k Image Cliques for Few-Shot Learning" GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference ...