Seminario 3


Ponente:  Juani Bermejo Vega (Grupo de Termodinamica y Informació Cuántica)

Titulo:  Quantum computing for machine learning and data science

Resumen:  Quantum computing is an emerging research field at the intersection of physics, computer science and applied mathematics. Quantum computers are devices that exploit coherent quantum phenomena to speed-up calculations. Quantum machine learning is a subfield of quantum computing that investigates the application of quantum computers algorithms for machine learning problems. This course will give an elementary introduction to quantum machine learning, and review a few examples of quantum algorithms for classification and clustering problems. In our first meeting, we will give a general introduction, and review quantum algorithms for solving linear systems of equations, Grover search and simulating sparse Hamiltonian dynamics.

El mini curso es accesible para los estudiantes de grado, a los que recomendamos encarecidamente que asistan 

Nos vemos a todos allí

DJM

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Dear all

The Quantum Thermodynamics and Computation group cordially invites you to the following seminar, continuing on the topic of  Quantum computing for machine learning and data science, by Juani Bermejo Vega 

Seminar 3

Date:  16 Junio, 2023

Time: 11:00 am

Location:  Computational Physics Laboratory, Department of Electromagnetism and Condensed Mater,  Ground Floor, Faculty of Science (next to the giant pendulum)


Speaker:  Juani Bermejo Vega (Quantum Thermodynamics and Computation group)

Title:  Quantum computing for machine learning and data science

Abstract:  Quantum computing is an emerging research field at the intersection of physics, computer science and applied mathematics. Quantum computers are devices that exploit coherent quantum phenomena to speed-up calculations. Quantum machine learning is a subfield of quantum computing that investigates the application of quantum computers algorithms for machine learning problems. This course will give an elementary introduction to quantum machine learning, and review a few examples of quantum algorithms for classification and clustering problems. In our first meeting, we will give a general introduction, and review quantum algorithms for solving linear systems of equations, Grover search and simulating sparse Hamiltonian dynamics.

This mini course is accessible to undergraduate students, whom we strongly encourage to attend.

See you all there

DJM.