Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Abstract. In this paper an exact and complete analysis of the Lloyd–Max’s algorithm and its initialization is carried out. An effective method for initialization of Lloyd–Max...
A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed...
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
— Most existing work uses dual decomposition and subgradient methods to solve network optimization problems in a distributed manner, which suffer from slow convergence rate prope...
Ali Jadbabaie, Asuman E. Ozdaglar, Michael Zargham