PROGRAM
Days: Thursday, January 12th Friday, January 13th Saturday, January 14th Sunday, January 15th
Thursday, January 12th
View this program: with abstractssession overviewtalk overview
Friday, January 13th
View this program: with abstractssession overviewtalk overview
09:00-09:30 Session 1: Registration and opening
Registration and opening
09:30-10:30 Session 2
09:30 | An Application of Stochastic Differential Equations to Evolutionary Algorithms ( abstract ) |
10:30-11:00Coffee Break
11:00-12:00 Session 3
11:00 | Runtime Analysis of a Discrete Particle Swarm Optimization Algorithm on Sorting and OneMax ( abstract ) |
12:00-13:30Lunch Break
13:30-15:30 Session 4
13:30 | Convergence of Factored Evolutionary Algorithms ( abstract ) |
14:30 | Analysis of the (1+1) EA on Subclasses of Linear Functions under Uniform and Linear Constraints ( abstract ) |
15:30-16:00Coffee Break
16:00-17:00 Session 5
16:00 | Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems ( abstract ) |
Saturday, January 14th
View this program: with abstractssession overviewtalk overview
10:00-10:30Coffee Break
10:30-11:30 Session 7
10:30 | On the Use of the Dual Formulation for Minimum Weighted Vertex Cover in Evolutionary Algorithms ( abstract ) |
11:30-12:30 Session 8
11:30 | Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling ( abstract ) |
12:30-14:00Lunch Break
14:00-16:00 Session 9
14:00 | Lower Bounds on the Run Time of the Univariate Marginal Distribution Algorithm on OneMax ( abstract ) |
15:00 | Analysis of the Clearing Diversity-Preserving Mechanism ( abstract ) |
16:00-16:30Coffee Break
16:30-17:30 Session 10
16:30 | Resampling vs Recombination: a Statistical Run Time Estimation ( abstract ) |
Sunday, January 15th
View this program: with abstractssession overviewtalk overview
09:00-11:00 Session 11
09:00 | Quality Gain Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions ( abstract ) |
10:00 | Qualitative and Quantitative Assessment of Step Size Adaptation Rules ( abstract ) |
11:00-11:30Coffee Break
11:30-12:30 Session 12
11:30 | On the Statistical Learning Ability of Evolution Strategies ( abstract ) |