888-384-7144 info@insidequantumtechnology.com

MIT and Xanadu Publish Paper On Quantum Classifiers as Trainable Quantum Circuits for Machine Learning Models.

By IQT News posted 17 Feb 2020

(SwissQuantumHub) A team of scientists at MIT and Xanadu has published a paper about quantum classifiers as trainable quantum circuits used as machine learning models.
The first part of the circuit implements a quantum feature map that encodes classical inputs into quantum states, embedding the data in a high-dimensional Hilbert space.
The second part of the circuit executes a quantum measurement interpreted as the output of the model. Usually, the measurement is trained to distinguish quantum-embedded data. They have proposed to instead train the first part of the circuit—the embedding—with the objective of maximally separating data classes in Hilbert space, a strategy they call quantum metric learning.

Subscribe to Our Email Newsletter

Stay up-to-date on all the latest news from the Quantum Technology industry and receive information and offers from third party vendors.

IQT Partner Program

Quantropi
DUSA
McAndrews
HKA
Aliro
RANDAEMON
Zapata
Quantum Xchange
Toshiba
Quintessence Labs
Keysight World
Post Quantum

Become an IQT partner

0