Presentation 1999/12/16
Warp-Robust Classification Function Learning Based on Linear Programming and Dynamic Programming
Tomtaka HIROSE, Yosinori KATAYAMA, Hiroaki SAKOE,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A new linear classification function learning algorithm is described for warp-robust pattern recognition. The algorithm involves learning cycle with linear programming based classification function calculation and dynamic programming based pattern warping. At each learning cycle, each of training patterns is warped so that resultant pattern is most inseparable with current classification function, and is used in the further learning cycles. The algorithm validity is established through a learning experiment.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) classification function / warp-robust learning / linear programming / dynamic programming
Paper # PRMU99-169
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Conference Information
Committee PRMU
Conference Date 1999/12/16(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Warp-Robust Classification Function Learning Based on Linear Programming and Dynamic Programming
Sub Title (in English)
Keyword(1) classification function
Keyword(2) warp-robust learning
Keyword(3) linear programming
Keyword(4) dynamic programming
1st Author's Name Tomtaka HIROSE
1st Author's Affiliation MITSUBISHI ELECTRIC()
2nd Author's Name Yosinori KATAYAMA
2nd Author's Affiliation Department of Intelligent Systems, Kyushu University
3rd Author's Name Hiroaki SAKOE
3rd Author's Affiliation Department of Intelligent Systems, Kyushu University
Date 1999/12/16
Paper # PRMU99-169
Volume (vol) vol.99
Number (no) 514
Page pp.pp.-
#Pages 8
Date of Issue