公开(公告)号：US20170300814A1

公开(公告)日：2017-10-19

申请号：US15394668

申请日：2016-12-29

Applicant: Google Inc.

Inventor： Tal Shaked ,  Rohan Anil ,  Hrishikesh Balkrishna Aradhye ,  Mustafa Ispir ,  Glen Anderson ,  Wei Chai ,  Mehmet Levent Koc ,  Jeremiah Harmsen ,  Xiaobing Liu ,  Gregory Sean Corrado ,  Tushar Deepak Chandra ,  Heng-Tze Cheng

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/084

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

公开(公告)号：US20170039483A1

公开(公告)日：2017-02-09

申请号：US14820751

申请日：2015-08-07

Applicant: Google Inc.

Inventor： Heng-Tze Cheng ,  Jeremiah Harmsen ,  Alexandre Tachard Passos ,  David Edgar Lluncor ,  Shahar Jamshy ,  Tal Shaked ,  Tushar Deepak Chandra

IPC: G06N99/00 ,  G06N5/04 ,  G06F17/30

CPC classification number: G06N99/005 ,  G06F17/30477 ,  G06F17/30864 ,  G06N5/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a factorization model to learning features of model inputs of a trained model such that the factorization model is predictive of outcome for which the machine learned model is trained.

Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于训练因子分解模型以学习训练模型的模型输入的特征，使得因式分解模型预测机器学习模型被训练的结果。