20 citations · 34 across the 5 of their papers we have counts for
5 papers
Feature Selection for Vertex Discriminant Analysis
Alfonso Landeros, Tong Tong Wu, Kenneth Lange
We revisit vertex discriminant analysis (VDA) from the perspective of proximal distance algorithms. By specifying sparsity sets as constraints that directly control the number of a…
Algorithms for Sparse Support Vector Machines
Alfonso Landeros, Kenneth Lange
Many problems in classification involve huge numbers of irrelevant features. Model selection reveals the crucial features, reduces the dimensionality of feature space, and improves…
Nonconvex Optimization via MM Algorithms: Convergence Theory
Kenneth Lange, Joong-Ho Won, Alfonso Landeros +1
The majorization-minimization (MM) principle is an extremely general framework for deriving optimization algorithms. It includes the expectation-maximization (EM) algorithm, proxim…
Extensions to the Proximal Distance Method of Constrained Optimization
Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou +1
The current paper studies the problem of minimizing a loss subject to constraints of the form , where is a closed set, c…
BioSimulator.jl: Stochastic simulation in Julia
Alfonso Landeros, Timothy Stutz, Kevin L. Keys +4
Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dyna…