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...
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, \...
Majorization-minimization algorithm for smooth Itakura-Saito non- negative matrix factorization. In International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011a.A. Lefe`vre, F. Bach, and C. Fe´votte, "Itakura-saito non- negative matrix factorization with group spa...
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...
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 【2】Ying Sun and Daniel P. Palomar. Majorization-Minimization Algorithm: Theory...
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 ...
Themmcg, Majorize-Minimize Conjugate Gradient algorithm. See documentation and [1] for details. No linesearch: the step is obtained from a close form formula without sub-iteration. No conjugacy choice: a conjugacy strategy is not necessary thanks to the subspace nature of the algorithms. Themmcg...
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 ...
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 ...