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Provable Exponential Quantum Speed-Up for Machine Learning

December 11 at 3:50 pm
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  • Plenary Talks
  • Mission City Ballroom
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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

Event Series Event Series (See All)
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

Details

Date:
December 11
Time:
3:50 pm - 4:10 pm
Series:
Plenary Talks
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Mission City Ballroom

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