US 12,462,290 B2
Utilizing additive decomposition for universal off-policy evaluation of digital content slate recommendations
Shreyas Chaudhari, Amherst, MA (US); Nikolaos Vlassis, San Jose, CA (US); Georgios Theocharous, San Jose, CA (US); and David Arbour, San Jose, CA (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Dec. 6, 2023, as Appl. No. 18/530,907.
Prior Publication US 2025/0191047 A1, Jun. 12, 2025
Int. Cl. G06Q 30/00 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0631 (2013.01) 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving historical slate data comprising observed rewards from selecting slate actions for a plurality of digital slots of a digital slate utilizing a first slate recommendation policy;
generating, for a second slate recommendation policy, a plurality of importance weights from the historical slate data by summing slot-level density ratios between the first slate recommendation policy and the second slate recommendation policy for the slate actions; and
generating a predicted reward distribution for the second slate recommendation policy by applying the plurality of importance weights to the historical slate data for the first slate recommendation policy.