About
Abstract
In this introduction to the foundations of quantum machine learning, we will dive into key concepts such as data encoding, feature map selection, and the comparison of different metrics for quantum kernel estimation. By the end of the session, students should be able to understand the basic steps and considerations in implementing and assessing quantum algorithms for machine learning.
Bio
Francesco Di Marcantonio
Francesco is a PhD student at CERN and University of the Basque Country. He studied at KTH and Politecnico di Torino and focuses on the simulation of Quantum Matter with Tensor Network Methods and other techniques related to Quantum Computation.
Roman Wixinger
Roman is a Software Engineer with a background in Physics. He studied at ETH Zurich and does research in Quantum Computing and Particle Physics at CERN and the University of Tokyo..
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The talk
Credits and licence
- Institution
- CERN
- Department
- CERN openlab summer student lecture programme
- Taught by
- Roman Luca Wixinger, Francesco Di Marcantonio
- Year
- 2023
- Language
- English
- Subjects
- Physics, Computer science
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed