Fast incremental learning for one-class support vector classifier using sample margin information

Pyo Jae Kim; Hyung Jin Chang; Jin Young Choi

doi:10.1109/ICPR.2008.4761720

Fast incremental learning for one-class support vector classifier using sample margin information

Pyo Jae Kim
, Hyung Jin Chang
, Jin Young Choi

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present a fast incremental one-class classifier algorithm for large scale problems. The proposed method reduces space and time complexities by reducing training set size during the training procedure using a criterion based on sample margin. After introducing the sample margin concept, we present the proposed algorithm and apply it to face detection database to show its efficiency and validity.

Original language	English
Title of host publication	2008 19th International Conference on Pattern Recognition
Publisher	IEEE
Pages	1-4
Number of pages	4
ISBN (Print)	978-1-4244-2175-6
DOIs	https://doi.org/10.1109/ICPR.2008.4761720
Publication status	Published - 11 Dec 2008
Event	2008 19th International Conference on Pattern Recognition - Tampa, FL, USA Duration: 8 Dec 2008 → 11 Dec 2008

Conference

Conference	2008 19th International Conference on Pattern Recognition
Period	8/12/08 → 11/12/08

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10.1109/ICPR.2008.4761720

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4761720

Cite this

@inproceedings{4f6ed9590e894415b683260a1282052b,

title = "Fast incremental learning for one-class support vector classifier using sample margin information",

abstract = "In this paper, we present a fast incremental one-class classifier algorithm for large scale problems. The proposed method reduces space and time complexities by reducing training set size during the training procedure using a criterion based on sample margin. After introducing the sample margin concept, we present the proposed algorithm and apply it to face detection database to show its efficiency and validity.",

author = "Kim, \{Pyo Jae\} and Chang, \{Hyung Jin\} and Choi, \{Jin Young\}",

year = "2008",

month = dec,

day = "11",

doi = "10.1109/ICPR.2008.4761720",

language = "English",

isbn = "978-1-4244-2175-6",

pages = "1--4",

booktitle = "2008 19th International Conference on Pattern Recognition",

publisher = "IEEE",

note = "2008 19th International Conference on Pattern Recognition ; Conference date: 08-12-2008 Through 11-12-2008",

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TY - GEN

T1 - Fast incremental learning for one-class support vector classifier using sample margin information

AU - Kim, Pyo Jae

AU - Chang, Hyung Jin

AU - Choi, Jin Young

PY - 2008/12/11

Y1 - 2008/12/11

N2 - In this paper, we present a fast incremental one-class classifier algorithm for large scale problems. The proposed method reduces space and time complexities by reducing training set size during the training procedure using a criterion based on sample margin. After introducing the sample margin concept, we present the proposed algorithm and apply it to face detection database to show its efficiency and validity.

AB - In this paper, we present a fast incremental one-class classifier algorithm for large scale problems. The proposed method reduces space and time complexities by reducing training set size during the training procedure using a criterion based on sample margin. After introducing the sample margin concept, we present the proposed algorithm and apply it to face detection database to show its efficiency and validity.

UR - https://ieeexplore.ieee.org/document/4761720/

U2 - 10.1109/ICPR.2008.4761720

DO - 10.1109/ICPR.2008.4761720

M3 - Conference contribution

SN - 978-1-4244-2175-6

SP - 1

EP - 4

BT - 2008 19th International Conference on Pattern Recognition

PB - IEEE

T2 - 2008 19th International Conference on Pattern Recognition

Y2 - 8 December 2008 through 11 December 2008

ER -

Fast incremental learning for one-class support vector classifier using sample margin information

Abstract

Conference

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