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Found 3 papers, 1 papers with code
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
To improve this estimate for KD, in this paper we introduce the concept of conditional mutual information (CMI) into the estimation of BCPD and propose a novel estimator called the maximum CMI (MCMI) method.
Conditional Mutual Information Constrained Deep Learning for Classification
The concepts of conditional mutual information (CMI) and normalized conditional mutual information (NCMI) are introduced to measure the concentration and separation performance of a classification deep neural network (DNN) in the output probability distribution space of the DNN, where CMI and the ratio between CMI and NCMI represent the intra-class concentration and inter-class separation of the DNN, respectively.
Dual Graph enhanced Embedding Neural Network for CTR Prediction
To solve these problems, we propose a novel module named Dual Graph enhanced Embedding, which is compatible with various CTR prediction models to alleviate these two problems.
