公开(公告)号：US20220366340A1

公开(公告)日：2022-11-17

申请号：US17319704

申请日：2021-05-13

Applicant: Microsoft Technology Licensing, LLC

Inventor： Tianyi CHEN ,  Jesus BARRERA RAMOS ,  Dhirendra BHUPATI ,  Muskan KUKREJA

IPC: G06Q10/06 ,  G06Q30/02 ,  G06F8/65

Abstract: A smart rollout recommendation system uses a modernization score that indicates a likelihood of accepting a change in an existing product to identify at least one tenant of a plurality of tenants eligible to receive the change and the timing of the rollout. The modernization score is generated using a set of attributes extracted from tenant profiles and a machine learning model.

公开(公告)号：US20210390384A1

公开(公告)日：2021-12-16

申请号：US16889775

申请日：2020-06-01

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Tianyi CHEN ,  Sheng YI ,  Yixin SHI ,  Xiao TU

IPC: G06N3/08 ,  G06N3/04

Abstract: The performance of a neural network (NN) and/or deep neural network (DNN) can limited by the number of operations being performed as well as management of data among the various memory components of the NN/DNN. A sparsity-inducing regularization optimization process is performed on a machine learning model to generate a compressed machine learning model. A machine learning model is trained using a first set of training data. A sparsity-inducing regularization optimization process is executed on the machine learning model. Based on the sparsity-inducing regularization optimization process, a compressed machine learning model is received. The compressed machine learning model is executed to generate one or more outputs.