Add to ORKGSequential sampling strategies based on Gaussian processes are now widely used for the optimization of problems involving costly simulations. But Gaussian processes can also generate parallel optimiza- tion strategies. We focus here on a new, parameter free, parallel expected improvement criterion for asynchronous optimization. An estimation of the criterion, which mixes Monte Carlo sampling and analytical bounds, is proposed. Logarithmic speed-ups are measured on 1 and 9 dimensional functions
During the last decade, Kriging-based sequential algorithms like EGO and its variants have become re...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
The sequential sampling strategies based on Gaussian processes are widely used for optimization of t...
Deliverable no. 2.1.1-BThe sequential sampling strategies based on Gaussian processes are widely use...
During the last decade, Kriging-based sequential algorithms like EGO and its variants have become re...
Budgeted optimization algorithms based on Gaussian processes have attracted a lot of attention as a ...
Budgeted optimization algorithms based on Gaussian processes have attracted a lot of attention as a ...
During the last decade, Kriging-based sequential algorithms like EGO and its variants have become re...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
Revised selected articles from the LION 6 Conference (Paris, Jan. 16-20, 2012), LNCS 7219, 978-3-642...
The sequential sampling strategies based on Gaussian processes are widely used for optimization of t...
Deliverable no. 2.1.1-BThe sequential sampling strategies based on Gaussian processes are widely use...
During the last decade, Kriging-based sequential algorithms like EGO and its variants have become re...
Budgeted optimization algorithms based on Gaussian processes have attracted a lot of attention as a ...
Budgeted optimization algorithms based on Gaussian processes have attracted a lot of attention as a ...
During the last decade, Kriging-based sequential algorithms like EGO and its variants have become re...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
This study addresses the stochastic optimization of a function unknown in closed form which can only...