sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 16-21, 2014

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Quantum Computing Paradigms for Probabilistic Inference and Optimization

SESSION: Invited Talks 1

EVENT TYPE: Invited Speakers

TIME: 10:30AM - 11:15AM

SESSION CHAIR: Robert F. Lucas

Presenter(s):Masoud Mohseni

ROOM:New Orleans Theater


Over the past 30 years, several computational paradigms have been developed based on the premise that the laws of quantum mechanics could provide radically new and more powerful methods of information processing. One of these approaches is to encode the solution of a computational problem into the ground state of a programmable many-body quantum Hamiltonian system. Although, there is empirical evidence for quantum enhancement in certain problem instances, there is not a full theoretical understanding of the conditions for quantum speed up for problems of practical interest, especially hard combinatorial optimization and inference tasks in machine learning. In this talk, I will provide an overview of quantum computing paradigms and discuss the progress at the Google Quantum Artificial Intelligence Lab towards developing the general theory and overcoming practical limitations. Furthermore, I will discuss two algorithms that we have recently developed known as Quantum Principal Component Analysis and Quantum Boltzmann Machine.

Chair/Presenter Details:

Robert F. Lucas (Chair) - Information Sciences Institute

Masoud Mohseni - Google

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