Conveners
Multivariate Analysis
- Oksana Shadura (University of Nebraska Lincoln (US))
In this talk, we will describe the latest additions to the Toolkit for Multivariate Analysis (TMVA), the machine learning package integrated into the ROOT framework. In particular, we will focus on the new deep learning module that contains robust fully-connected, convolutional and recurrent deep neural networks implemented on CPU and GPU architectures. We will present performance of these new...
Cross validation, an important tool for optimising and understanding generalisation performance of large models (many tunable parameters), was recently introduced in TMVA. Currently implemented to estimate model performance, developments are ongoing for model selection. This talk will give an introduction to what CV is and how it is used in TMVA, with particular focus on HEP...
TMVA has been a pioneering effort which set a milestone for machine-learning (ML) in high-energy physics (HEP) more than ten years ago and remains in use in numerous analyses of LHC experiments.
On the other hand, the ML landscape explosively evolved during these years and - as industry stepped in - ML became suddenly one of the most active fields in science. This talk discusses how TMVA can...
