Seminarium: Advances in Machine Learning tools in High Energy Physics
- Datum: 2017-10-26 kl 15:15 – 16:30
- Plats: Ångströmlaboratoriet Å12167
- Föreläsare: David Rousseau (LAL-Orsay)
- Kontaktperson: Elin Bergeås Kuutmann
- Telefon: 018-471 3828
Weekly seminar in high energy physics about machine learning tools.
Machine Learning (known as Multi Variate Analysis) has been used somewhat in HEP in the nineties, then at the Tevatron and recently at the LHC. However with the birth of internet giants at the turn of the century, there has been an explosion of Machine Learning tools in the industry, HEP being left behind. A collective effort has been started in recent years to bring state-of-the-art Machine Learning tools to high energy physics, and to promote collaborations between HEP physicists and Machine Learning specialists.
This seminar will give a tour d’horizon of Machine Learning in HEP: review of tools beyond root-TMVA ; example of applications, some usable immediately (e.g. cross validation, novelty detection), some in a (possibly distant) future (e.g. deep learning, image vision, Generative Adversarial Networks) ; recent and future HEP ML competitions ; setting up frameworks for Machine Learning collaborations.