Algorithm 2: Expectation-Minimization Algorithm Input: Model p_{X|\Theta}(\bold x|\theta) , Max Iteration Limit N, Initial Guess \theta_0 for k = 0,…,N-1 and if model is not converged do: Compute q(\bold z) , according to q(\bold z)=\frac{p_{X,Z|\Theta}(\bold x, \...
MM algorithm - Wikipedia [1] Julien Mairal, Optimization with first-order surrogate functions. ICML, 2013. [2] Lu et al., Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm, IEEE Trans. Image Processing, 2016. minX∑i=1min(m,n)h(σi(X))+f(X) h(σi...
However, the objective functions (the entropy loss function) can be bounded above by a sequence of separable functions-we proposed a novel estimation algorithm based on this property under the Majorization-Minimization (MM) algorithmic framework. The proposed MM algorithm exhibited very lo...
T. Zhang, A majorization-minimization algorithm for the Karcher mean of positive definite matrices, arXiv preprint arXiv:1312.4654 (2013).T. Zhang. A majorization-minimization algorithm for computing the Karcher mean of positive definite matrices. SIAM Journal on Matrix Analysis and Applications, 38...
另外,文献【5】将Majorization-Minimization进行了推广,即Generalized MM: 懂得Majorization-Minimization这个优化框架很重要,很多迭代类的算法均基于此,否则无法透彻的理解一些算法。 参考文献: 【1】谷鹄翔.IteratedSoft-ThresholdingAlgorithm[Report,slides]. http://www.sigvc.org/bbs/thread-41-1-2.html ...
The proposed framework utilizes the majorization-minimization (MM) algorithm as its core optimization engine. In the case of penalized regression models, the resulting algorithms employ iterated soft-thresholding, implemented componentwise, allowing for fast and stable updating that avoids the need for ...
另外,文献【5】将Majorization-Minimization进行了推广,即Generalized MM: 懂得Majorization-Minimization这个优化框架很重要,很多迭代类的算法均基于此,否则无法透彻的理解一些算法。 参考文献: 【1】谷鹄翔.IteratedSoft-ThresholdingAlgorithm[Report,slides]. http://www.sigvc.org/bbs/thread-41-1-2.html ...
Then you can run the algorithm res = qmm.mmmg([data_adeq, prior], init, max_iter=200) where[data_adeq, prior]{.sourceCode} means that the two objective functions are summed. For more details, seedocumentation. Contribute Source code:https://github.com/forieux/qmm ...
optimize the phase shifts of the STAR-RIS in the WET phase by the Majorization-Minimization (MM) algorithm and the complex circle manifold (CCM) ... W Du,Z Chu,G Chen,... - 《Vehicular Technology IEEE Transactions on》 被引量: 0发表: 2023年 MM algorithms for distance covariance based ...
This monotonicity of f(x_k) in k is an important property of the majorization-minimization and will be used in our analysis. The following two lemmas show that the parameters M and \eta in the algorithm are upper-bounded, and hence Lines 9 and 15 are executed only a finite number of ...