Purdue University Collaboration Advance Quantum Machine Learning
Discovery Park to host International Quantum Machine Learning and Data Analytics Workshop
Excerpts and salient points ~
+ With the rapid development of quantum computers, a number of quantum algorithms have been developed and tested on both superconducting qubits-based machines and ion trap hardware. Quantum machine learning is expected to be a potential application of quantum computers in the near future. Many quantum machine learning algorithms have been proposed to speed up classical machine learning by quantum computers. At the same time, deep learning has shown great power in solving real-world problems.
Purdue Quantum Science and Engineering Institute in partnership with the Integrative Data Science Initiative will host a Quantum Machine Learning and Data Analytics Workshop on Sept. 5-6 in the Hall for Discovery and Learning Research. https://www.purdue.edu/data-science/quantum-machine-learning/
+ “This workshop aims to bring together international leading experts in this new field of quantum machine learning,” says Sabre Kais, professor of chemistry at Purdue. Kais is chair of the organizing committee along with members Travis Humble of Oak Ridge National Laboratory and Jason Tuner of the Entanglement Institute. Discussions will center on the recent development of quantum algorithms to perform machine learning tasks on large-scale scientific data sets for various industrial and technological applications. This will aid in solving challenging problems in science and engineering.
+ “Quantum machine learning has the potential to provide a computational advantage to many areas of science and technology,” says Tomás Díaz de la Rubia, vice president for Discovery Park. “We are pleased to be able to host this workshop and its cadre of talented experts in the field.”
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