Extreme learning machine with sparse connections

Extreme learning machine with sparse connections

The thesis is in the field of machine learning, and specifically studies the recent emerging algorithm, Extreme Learning Machine (ELM). Unlike previous ELM implementations, in which hidden nodes are in full connection with the input ones, we present the ELM with sparse connections. In one way, it re...

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Bibliographic Details
Main Author: Bai, Zuo
Other Authors: Wang Dan Wei
Format: Theses and Dissertations
Language:English
Published: 2015
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:https://hdl.handle.net/10356/65656
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Institution: Nanyang Technological University
Language: English
Description
Summary:The thesis is in the field of machine learning, and specifically studies the recent emerging algorithm, Extreme Learning Machine (ELM). Unlike previous ELM implementations, in which hidden nodes are in full connection with the input ones, we present the ELM with sparse connections. In one way, it reduces the storage space and testing time, while providing better scalability for large-scale applications. In the other way, the sparse connections make it especially suitable and efficient for locally correlated applications, such as image processing, speech recognition, etc.

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