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Structural risk minimization for quantum linear classifiers
Manage episode 367157544 series 3445409
Content provided by Mark McGuire. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mark McGuire or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
You can read the paper here:
https://quantum-journal.org/papers/q-2023-01-13-893/
Or if you want to read a summary, try my wordpress or medium!
The paper summarized here studies how to balance between training accuracy and generalization performance (also called structural risk minimization) for two prominent QML models using relationships to classical models.
40 episodes
Share
Manage episode 367157544 series 3445409
Content provided by Mark McGuire. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mark McGuire or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
You can read the paper here:
https://quantum-journal.org/papers/q-2023-01-13-893/
Or if you want to read a summary, try my wordpress or medium!
The paper summarized here studies how to balance between training accuracy and generalization performance (also called structural risk minimization) for two prominent QML models using relationships to classical models.
40 episodes
All episodes
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Similar to Quantum Computing Summaries
A fun-filled discussion of the big, mind-blowing, unanswered questions about the Universe. In each episode, Daniel Whiteson (a Physicist who works at CERN) and Jorge Cham (a popular online cartoonist) discuss some of the simple but profound questions that people have been wondering about for thousands of years, explaining the science in a fun, shorts-wearing and jargon-free way.
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continue reading
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…
continue reading
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…
continue reading
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…
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