Kenneth Lange
UCLA
3:45 PM
127 Hayes-Healy Center
A tea will precede the event at 3:15 pm in 101A Crowley Hall.
Examples of MM Optimization Algorithms
This talk will survey applications of the MM principle, a framework for constructing monotone optimization algorithms in high-dimensional models. The MM principle transfers optimization from the objective function to a surrogate function and turns a hard optimization problem into a sequence of simpler ones. MM simplifies matters by: (a) separating the variables of a problem, (b) avoiding large matrix inversions, (c) linearizing a problem, (d) restoring symmetry, (e) dealing with equality and inequality constraints gracefully, and (f) turning a non-differentiable problem into a smooth problem.
Click HERE for zoom link (nd.edu access only)
View Poster