Speeding up iterative polyhedral schedule optimization with surrogate performance models
S Ganser, A Größlinger, N Siegmund, S Apel… - ACM Transactions on …, 2018 - dl.acm.org
Iterative program optimization is known to be able to adapt more easily to particular
programs and target hardware than model-based approaches. An approach is to generate …
programs and target hardware than model-based approaches. An approach is to generate …
[PDF][PDF] Supplementary material for Bias in the Intervention in Prediction Measure in Random Forests
S Nembrini - 2018 - researchgate.net
Supplementary material for Bias in the Intervention in Prediction Measure in Random Forests
Page 1 Supplementary material for Bias in the Intervention in Prediction Measure in Random …
Page 1 Supplementary material for Bias in the Intervention in Prediction Measure in Random …
[PDF][PDF] On what to permute in test-based approaches for variable selection in Random Forests.
S Nembrini - 2018 - researchgate.net
Motivation: Random forests (RF) is a popular machine learning algorithm which has become
a standard tool in bioinformatics, particularly because it provides variable importance …
a standard tool in bioinformatics, particularly because it provides variable importance …