Invention Grant
- Patent Title: Bi-scaled deep neural networks
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Application No.: US16593284Application Date: 2019-10-04
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Publication No.: US11263518B2Publication Date: 2022-03-01
- Inventor: Swagath Venkataramani , Shubham Jain , Vijayalakshmi Srinivasan , Leland Chang
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Stosch Sabo
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/063

Abstract:
A method is provided for forming a Deep Neural Network (DNN). The method includes quantizing deep learning data structures of the DNN into at least two modes using at least two scale factors, respectively. Each of the at least two modes corresponds to a respective one of the at least two scale factors. The method further includes identifying which of the at least two scale factors to use for a given one of the data structures based on a data distribution of the given one of the data structures. The quantizing step includes identifying when a tail of the given one of the data structures starts by (i) building a histogram of values in the given one of the data structures using successive bins; (ii) identifying a ratio of density between the successive bins; and (iii) checking whether the ratio of density is greater than a ratio of density threshold.
Public/Granted literature
- US20210103799A1 BI-SCALED DEEP NEURAL NETWORKS Public/Granted day:2021-04-08
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