Quantum Machine Learning

Recent strides in quantum computing have raised the prospects that near term quantum devices can expediently solve computationally intractable problems in simulation, optimization and machine learning. The opportunities that quantum computing raises for machine learning is hard to understate. The goal of this workshop is, through a series of invited and contributed talks, survey the major results in this new area and facilitate increased dialog between researchers within this field. We will be accepting contributed talks as well. The deadline for submission is Oct 24. An abstract and link to the paper should be provided. We will provide feedback on submissions before the deadline for early registration for NIPS. All talks given will not be published in the proceedings and will be reviewed by the conference organizers. Please sent all…

Link to Full Article: Quantum Machine Learning

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