Quantum-inspired machine learning

In recent years, the need for more powerful computers has grown due to the availability of large amounts of data and significant progress in the artificial intelligence and machine learning fields. However, making computer chips smaller and more powerful is becoming increasingly harder and more expensive. To address this challenge, we are exploring a new approach called Quantum-inspired Machine Learning (QiML) to reproduce quantum machine learning using regular computing devices. Our project will examine how well QiML works compared to traditional methods, focusing on applications in telecommunications. By using these new techniques, our goal is to help our partner organization stay ahead in the technology field, offering them new ways to use the advantages of quantum concepts without needing actual quantum computers, thus leading to significant improvements in their products and services portfolio.

Faculty Supervisor:

Bassant Selim;Éric Granger

Student:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program: