US 11,893,489 B2
Data retrieval using reinforced co-learning for semi-supervised ranking
Shibi He, Urbana, IL (US); Yanen Li, Los Angeles, CA (US); and Ning Xu, Irvine, CA (US)
Assigned to SNAP INC., Santa Monica, CA (US)
Filed by Snap Inc., Santa Monica, CA (US)
Filed on Oct. 24, 2022, as Appl. No. 17/972,459.
Application 17/972,459 is a continuation of application No. 16/448,749, filed on Jun. 21, 2019, granted, now 11,544,553.
Prior Publication US 2023/0053009 A1, Feb. 16, 2023
Int. Cl. G06F 18/24 (2023.01); G06F 18/20 (2023.01); G06N 3/08 (2023.01); G06N 3/045 (2023.01)
CPC G06N 3/08 (2013.01) [G06F 18/24 (2023.01); G06F 18/295 (2023.01); G06N 3/045 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
classifying, by a trained classifier, unlabeled data from a dataset, wherein the classifier includes a neural network;
providing iteratively, by the classifier to a policy gradient function, a reward signal for data/query pairs, wherein the reward signal is a combination of a normalized discounted cumulative gain and a discriminative score output by the classifier;
transferring, by the classifier to a ranker, learning from the classifying, wherein the ranker includes a neural network;
training, by the policy gradient function, the ranker; and
ranking, by the trained ranker, data from the dataset based on a query.