Method and system for incremental machine learning based on transparent computing

A machine learning and transparent computing technology, applied in the field of machine learning, to achieve the effect of reducing system delay, improving user experience, and reducing the amount of calculation

Active Publication Date: 2018-05-08
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide an incremental machine learning method and system based on transparent computing to avoid compatibility problems caused by multi-client differences and alleviat

Method used

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  • Method and system for incremental machine learning based on transparent computing
  • Method and system for incremental machine learning based on transparent computing
  • Method and system for incremental machine learning based on transparent computing

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Embodiment Construction

[0028] Such as figure 1 As shown, the framework of the system of the present invention is as figure 1 shown. It mainly includes three parts: transparent server, transparent client, and edge node. Training data can be obtained from three parts, but data training can only be performed on transparent servers and edge nodes with strong computing power.

[0029] The network configuration in the transparent server and the transparent client stores the communication information of all edge nodes from the client to the transparent server. Based on the test model on the transparent client, the transparent client can conduct user testing, and users can give user feedback on the test results to revise their correctness. Transparent clients, edge nodes and transparent servers can all collect data. Once the data is collected at the transparent client, it can send the collected data to the edge nodes or transparent servers through the network. The collected data will be stored in the me...

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Abstract

The invention discloses a method and a system for incremental machine learning based on transparent computing. An incremental machine learning framework based on transparent computing is used, so thatthe system can perform machine learning on the premise of low network dependence. Training data is split and processed, so that time consumption of machine learning is greatly reduced on the premiseof ensuring test accuracy, and machine learning efficiency is improved. In addition, through incremental feedback learning, accuracy of machine learning is continuously improved.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to an incremental machine learning method and system based on transparent computing. Background technique [0002] With the popularity of mobile networks and various lightweight clients, the Internet of Things is constantly changing our daily lives. Various IoT applications such as smartphones, wearable devices, and mobile sensors have been widely used in fields such as medical care, smart home, environmental monitoring, and intelligent transportation. Traditionally, lightweight clients only have the ability to collect and display data. However, in many cases, in order to ensure real-time performance, we prefer to make the client have some functional functions, such as facial recognition, object detection, etc., which do not need to transmit data to the server for processing. In addition, in some areas with poor network connections such as tunnels and remote places, we hope that th...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06N99/00H04L29/06
CPCG06F11/3688G06N20/00H04L67/01
Inventor 梁中鹤郭克华
Owner CENT SOUTH UNIV
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