Mittagsseminar (in cooperation with A. Steger, D. Steurer and B. Sudakov)

Date and Time: Tuesday, December 04, 2012, 12:15 pm

Duration: 30 minutes

Location: OAT S15/S16/S17

Speaker: Sebastian Stich

Variable Metric Random Pursuit

A continuous function f is to be minimized. Similar as in the discrete setting, people often use Randomized Search Heuristics for this task. While they often give good results in practice, most of them lack a thorough theoretical convergence analysis.

In this talk, we present and analyze Variable Metric Random Pursuit. This is an iterative algorithm where in every step a new approximation is calculated by searching along a randomly chosen direction. However, typically not every direction yields the same progress. The algorithm tries to "learn" successful search directions and samples them more often.

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