5 citations · 16 across the 22 of their papers we have counts for
4 papers · 1 filter
Fixed Point Algorithm for Solving Nonmonotone Variational Inequalities in Nonnegative Matrix Factorization
Hideaki Iiduka, Shizuka Nishino
Nonnegative matrix factorization (NMF), which is the approximation of a data matrix as the product of two nonnegative matrices, is a key issue in machine learning and data analysis…
Incremental and Parallel Machine Learning Algorithms with Automated Learning Rate Adjustments
Kazuhiro Hishinuma, Hideaki Iiduka
The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates must be determined be…
Two Stochastic Optimization Algorithms for Convex Optimization with Fixed Point Constraints
Hideaki Iiduka
Two optimization algorithms are proposed for solving a stochastic programming problem for which the objective function is given in the form of the expectation of convex functions a…
Proximal Point Algorithms for Nonsmooth Convex Optimization with Fixed Point Constraints
Hideaki Iiduka
The problem of minimizing the sum of nonsmooth, convex objective functions defined on a real Hilbert space over the intersection of fixed point sets of nonexpansive mappings, onto…