Massoud Babaie-Zadeh , Christian Jutten, A general approach for mutual information minimization and its application to blind source separation, Signal Processing, v.85 n.5, p.975-995, May 2005 [doi>10.1016/j.sigpro.2004.11.021]Babaie-Zadeh, M., Jutten, C.: Mutual information minimization: ...
网络互信息最小 网络释义 1. 互信息最小 3.2.2.2互信息最小(Mutual Information Minimization)31-32 3.2.2.3 极大似然估计(Maximum Likelihood Estimation)32 3.2.3 快速... cdmd.cnki.com.cn|基于2个网页
PDF Download BibTex Mutual information (MI) minimization has gained considerable interests in various machine learning tasks. However, estimating and minimizing MI in high-dimensional spaces remains a challenging problem, especially when only samples, rather than distribution forms, are acces...
Mutual information (MI) minimization has gained considerable interests in various machine learning tasks. However, estimating and minimizing MI in high-dimensional spaces remains a challenging problem, especially when only samples, rather than distribution forms, are accessible. Previous works mainly focus...
Rgb-d saliency detec-tion via cascaded mutual information minimization Info3d: Representation learning on 3d ob-jects using mutual information maximization and contrastive learning. 3.模型与方法 3.1 模型架构 如图所示,提出的网络架构包括三个模块,PAN、MS图像的特征提取模块,互信息约束模块,和基于INN(可逆神...
The necessary condition for detection operators to represent the information optimal detection is satisfied for M-ary symmetric quantum-state signals by the detection operators derived from the quantum minimax strategy while its purpose is a minimization of the error probability. The true maximum mutual...
Active learning reduces the annotation cost of machine learning by selecting and querying informative unlabeled samples. Semi-supervised active learning methods can considerably utilize the regional information of unlabeled samples, and thus, more effectively select valuable samples. Existing semi-supervised ...
(SCSeg). The performance gain benefits from two techniques—perturbation consistency and mutual information regularization. Perturbation consistency enforces the output consistency between the uncorrupted and perturbed features. Mutual information regularization adopts a mutual information loss to ensure the ...
requiresonlyinformationIforrepresenting anelementofX Alternative:fixedD,optimalI Algorithm ConstrainedMinimization LagrangeMultipliertorepresent tradeoff (,) M FMPDIλ=+ ((),(|))FtPtxDIγλ=+ Minimization 0,0 ()(|) FF tPtx δδ δγδ
update mi_minimization Feb 10, 2022 CLUB This repository contains source code to our ICML2020 paper: CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information CLUB is a sample-based estimator to mutual information (MI), which can not only provide reliable upper bound MI estimation, but ...