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Found 2 papers, 1 papers with code
Active Learning of Ordinal Embeddings: A User Study on Football Data
We adapt an entropy-based active learning method with recent work from triplet mining to collect easy-to-answer but still informative annotations from human participants and use them to train a deep convolutional network that generalizes to unseen samples.
Oracle Guided Image Synthesis with Relative Queries
Isolating and controlling specific features in the outputs of generative models in a user-friendly way is a difficult and open-ended problem.
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