Deep Parameter Confjguration
Lars Kotthofg
University of British Columbia larsko@cs.ubc.ca Dagstuhl Seminar Algorithm Selection and Confjguration
1 / 4
Deep Parameter Confjguration Lars Kotthofg University of British - - PowerPoint PPT Presentation
Deep Parameter Confjguration Lars Kotthofg University of British Columbia larsko@cs.ubc.ca Dagstuhl Seminar Algorithm Selection and Confjguration 1 / 4 Big Picture Algorithm Deep Parameters Exposed Parameters Algorithm Automatic
University of British Columbia larsko@cs.ubc.ca Dagstuhl Seminar Algorithm Selection and Confjguration
1 / 4
Algorithm Deep Parameters Exposed Parameters Algorithm Automatic Confjgurator Best Confjguration report performance propose confjguration
2 / 4
Levels of PbO:
Level 4: Make no design choice prematurely that cannot be justified compellingly. Level 3: Strive to provide design choices and alternatives. Level 2: Keep and expose design choices considered during software development. Level 1: Expose design choices hardwired into existing code (magic constants, hidden parameters, abandoned design alternatives). Level 0: Optimise settings of parameters exposed by existing software.
Hoos & Hutter: Programming by Optimization 12
3 / 4
▷ Automatic parameter extraction, Wu, Fan, Westley Weimer,
Mark Harman, Yue Jia, and Jens Krinke. “Deep Parameter Optimisation.” In Proceedings of the 2015 Annual Conference
’15. New York, NY, USA: ACM, 2015.
▷ Automatic confjguration, Hutter, Frank, Holger H. Hoos, and
Kevin Leyton-Brown. “Sequential Model-Based Optimization for General Algorithm Confjguration.” In LION 5, 507–23, 2011.
4 / 4