… Spectral Conditional Mutual Information (SPEC_CMI) which formulates the mRMR feature
selection criteria into a semi-definite programming model and solves it via spectral relaxation. …

… by maximizing an estimate of the mutual information (MI) between different views … model
from Section 3.1 adversarially. We model g1 with the same RealNVP architecture as in the first …

… model based on mutual information estimation without relying on image reconstruction or
image generation. Mutual information … is to perform dimensionality reduction while keeping the …

… mutual information do not require direct knowledge of any conditional densities. To establish
an initial lower bound on mutual information, … restrict our model to pρ(yi|xi) = N(ρix, √1 − ρ2 …

… means that if the amount of data for which to train a model is fixed, then increasing
dimensionality can lead to overfitting. This issue can be avoided by bringing in exponentially more …

… Lots of feature selection methods based on low-order mutual information [9,10,11,12… using
low-order mutual information is Mutual Information Maximum (MIM) [9] that applies information …

… ) limit their performance on dealing with high-dimensional … mutual information. Firstly, an
effective swarm initialization strategy based on label correlation is developed, making full use …

… methods for variational mutual information estimation. We first show that variational mutual
information estimation can … We train all models for 20k iterations, with the ground truth mutual …

… features using as a score the conditional mutual information (… mutual information of a feature
set and the prediction error, which, of course, will depend on the specific choice of the model …

… Following the inductive setup in [16], on Reddit, we feed posts made in the first 20 days
into the model for training, while the remaining are used for testing (with 30% used for validation); …