Provable Exponential Quantum Speed-Up for Machine Learning

December 11 at 3:50 pm
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Achieving a provable exponential quantum speedup for an important machine learning task has for long been a central research goal. This talk outlines a recent algorithmic research result showing that there is indeed a provable exponential separation between quantum and quantum-inspired classical algorithms for the basic problem of solving linear systems, given that the system matrix is well-conditioned and sparse.
Ulrich Hoff, Quantum Engagement Specialist, Kvantify
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Featured Speaker(s):
Ulrich Hoff

Ulrich Hoff

Quantum Engagement Specialist Kvantify
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Provable Exponential Quantum Speed-Up for Machine Learning

December 11 @ 3:50 pm - 4:10 pm

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Featured Speaker(s):
Ulrich Hoff

Ulrich Hoff

Quantum Engagement Specialist Kvantify

Achieving a provable exponential quantum speedup for an important machine learning task has for long been a central research goal. This talk outlines a recent algorithmic research result showing that there is indeed a provable exponential separation between quantum and quantum-inspired classical algorithms for the basic problem of solving linear systems, given that the system matrix is well-conditioned and sparse.


Ulrich Hoff, Quantum Engagement Specialist, Kvantify

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Date:
December 11
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3:50 pm - 4:10 pm
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