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기록

TECHNIQUES FOR ADAPTIVE MULTI-LEVEL RECOMMENDATION USING HIERARCHICAL MIXTURE-OF-EXPERTS FRAMEWORK

발명심사 중
20청구항 · 3 독립항
§ Ⅰ

개요

발명자

Maryam ESMAEILI; Justin Derrick BASILICO; Christoph KOFLER; Inbar NAOR; Jiangwei PAN; Jin WANG

IPC 분류

G6F 16/9535H4N 21/466

CPC 분류

G6F16/9535H4N21/4668

Techniques for adaptive multi-level recommendation include processing input features to generate pre-processed input features, processing the input features and the pre-processed input features using a plurality of expert models to generate expert outputs, mixing the input features and the expert outputs to generate mixed expert outputs, processing the mixed expert outputs using a first model of the hierarchical model to generate intermediate outputs, and processing the mixed expert outputs and the intermediate outputs using a second model of the hierarchical model to generate a final output.

원문 (중국어)

Techniques for adaptive multi-level recommendation include processing input features to generate pre-processed input features, processing the input features and the pre-processed input features using a plurality of expert models to generate expert outputs, mixing the input features and the expert outputs to generate mixed expert outputs, processing the mixed expert outputs using a first model of the hierarchical model to generate intermediate outputs, and processing the mixed expert outputs and the intermediate outputs using a second model of the hierarchical model to generate a final output.