Performance Evaluation for Four Types of Machine Learning Algorithms Using Educational Open Data

2019 ◽  
pp. 281-289
Author(s):  
Yuki Terawaki ◽  
Teruhiko Unoki ◽  
Toshiyasu Kato ◽  
Yasushi Kodama
Keyword(s):  
Machine Learning ◽  
Performance Evaluation ◽  
Learning Algorithms ◽  
Open Data ◽  
Machine Learning Algorithms

Performance Evaluation of Different Machine Learning Algorithms in Prediction of Pandemic in Early Stages

2021 ◽  
Vol 34 (01) ◽  
Author(s):  
Hemalatha S ◽  
◽  
Nivedha S ◽  
Dr. M Sangeetha ◽  
Dr. K. E Kannammal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Performance Evaluation ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Early Stages

scholarly journals Accelerating End-to-End Deep Learning for Particle Reconstruction using CMS open data

2021 ◽  
Vol 251 ◽  
pp. 03057
Author(s):  
Michael Andrews ◽  
Bjorn Burkle ◽  
Shravan Chaudhari ◽  
Davide Di Croce ◽  
Sergei Gleyzer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Top Quark ◽  
Learning Algorithms ◽  
Open Data ◽  
High Energy ◽  
Machine Learning Algorithms ◽  
Multiple Gpus ◽  
Event Identification ◽  
End To End

Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit from the use of machine learning. Incorporating these computational tools in the experimental framework presents new challenges. This paper reports on the implementation of the end-to-end deep learning with the CMS software framework and the scaling of the end-to-end deep learning with multiple GPUs. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation for particle and event identification. We demonstrate the end-to-end implementation on a top quark benchmark and perform studies with various hardware architectures including single and multiple GPUs and Google TPU.

Sign in / Sign up

Export Citation Format

Share Document