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Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy
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$a Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy 215 $a 8 s. $c E 463 -1
$1 001 cav_un_epca*0493925 $1 011 $a 1613-0073 $1 200 1 $a ITAT 2018: Information Technologies – Applications and Theory. Proceedings of the 18th conference ITAT 2018 $v S. 72-79 $1 210 $a Aachen $c Technical University & CreateSpace Independent Publishing Platform $d 2018 $1 225 $a CEUR Workshop Proceedings $v V-2203 $1 702 $4 340 $a Krajči $b S. 610 $a Gradient boosting 610 $a Random forest 610 $a Black-box optimization 610 $a Surrogate model 610 $a Benchmarking 700 -1
$3 cav_un_auth*0339112 $a Pitra $b Zbyněk $i Oddělení strojového učení $j Department of Machine Learning $p UIVT-O $w Department of Machine Learning $T Ústav informatiky AV ČR, v. v. i. 701 -1
$3 cav_un_auth*0350450 $a Repický $b Jakub $i Oddělení strojového učení $j Department of Machine Learning $p UIVT-O $w Department of Machine Learning $T Ústav informatiky AV ČR, v. v. i. 701 -1
$3 cav_un_auth*0100761 $a Holeňa $b Martin $i Oddělení strojového učení $j Department of Machine Learning $p UIVT-O $w Department of Machine Learning $T Ústav informatiky AV ČR, v. v. i. 856 $9 RIV $u http://ceur-ws.org/Vol-2203/72.pdf
Number of the records: 1