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GroupIM: A Mutual Information Maximization Framework for Neural Group Recomme...
We study the problem of making item recommendations to ephemeral groups, which comprise users who purchase very few (or no) items together. -
Self-Supervised Alignment with Mutual Information
The dataset is used for training a language model to follow behavioral principles without the use of preference labels, demonstrations, or human oversight. -
Synthetic Dataset
The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs... -
Multi-modal volume registration by maximization of mutual information
Multi-modal volume registration by maximization of mutual information.