Google llc (20250005656). Uncertainty Informed Automatic Bidding: Difference between revisions
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==Inventor(s)== | ==Inventor(s)== | ||
[[:Category:Alexander Kerelsky of New York NY | [[:Category:Alexander Kerelsky of New York NY US|Alexander Kerelsky of New York NY US]][[Category:Alexander Kerelsky of New York NY US]] | ||
[[:Category:Sergiu Ion Goschin of Mountain View CA | [[:Category:Sergiu Ion Goschin of Mountain View CA US|Sergiu Ion Goschin of Mountain View CA US]][[Category:Sergiu Ion Goschin of Mountain View CA US]] | ||
[[:Category:Dong Lin of Mountain View CA | [[:Category:Dong Lin of Mountain View CA US|Dong Lin of Mountain View CA US]][[Category:Dong Lin of Mountain View CA US]] | ||
[[:Category:Jie Han of San Jose CA | [[:Category:Jie Han of San Jose CA US|Jie Han of San Jose CA US]][[Category:Jie Han of San Jose CA US]] | ||
==Uncertainty Informed Automatic Bidding== | ==Uncertainty Informed Automatic Bidding== | ||
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This abstract first appeared for US patent application 20250005656 titled 'Uncertainty Informed Automatic Bidding | This abstract first appeared for US patent application 20250005656 titled 'Uncertainty Informed Automatic Bidding | ||
==Original Abstract Submitted== | ==Original Abstract Submitted== | ||
Latest revision as of 03:45, 25 March 2025
Uncertainty Informed Automatic Bidding
Organization Name
Inventor(s)
Alexander Kerelsky of New York NY US
Sergiu Ion Goschin of Mountain View CA US
Dong Lin of Mountain View CA US
Uncertainty Informed Automatic Bidding
This abstract first appeared for US patent application 20250005656 titled 'Uncertainty Informed Automatic Bidding
Original Abstract Submitted
this technology generally relates to a method for leveraging a measure of bidding model uncertainty to directly improve automatic bidding. the methods may include measuring the inherent uncertainty of automatic bidding models using techniques, such as quantile regression. further, the measure of bidding model uncertainty may be incorporated into bid formulas to inform the generated bids for an auction. the method may be further formulated to modify the bids to be more conservative when the bidding model uncertainty is higher. once the uncertainty level of the bidding model is reduced to a more stable level, the bidding method will resume generating bids with more efficiency.
