Matching Networks for One Shot Learning
Classify a new example from a list of other examples (without definitive categories) and with low-data per classification task, but lots of data for lots of similar classification tasks - it seems better than siamese networks. To sum up: with Matching Networks, you can optimize…
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Matching Networks for One Shot Learning arxiv.org
Interesting way of doing one-shot learning with low-data by using an attention mechanism and a query to compare an image to other images for classification.
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Prototypical Networks for Few-shot Learning arxiv.org
Use a distance metric in the loss to determine to which class does an object belongs to from a few examples.
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Cooperative Training of Descriptor and Generator Networks ieeexplore.ieee.org
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. [All Versions]. This paper studies the cooperative training of two generative models for image modeling and synthesis. Both models are parametrized by convolutional neural networks (ConvNets). The first model…
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Ensemble Learning Intro machine-learning.martinsewell.com
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Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same… proceedings.neurips.cc
NeurIPS'18, 2018. [All Versions]. Maching the learned pattern of neurons in different neural networks.
Education › Papers > Other: “Classify a new example from a list of other examples (without definitive categories) and with low-data per classification task, but lots of data for lots of similar classification tasks - it seems better than siamese networks. To sum up: with Matching Networks, you can optimize…”