On cone optimization approaches for semi-supervised support vector machines(S3VM)

Faizan Ahmed; Muhammad Faisal Iqbal; Ayesha Rafiq

doi:10.1109/ICOMET.2019.8673478

On cone optimization approaches for semi-supervised support vector machines(S3VM)

Faizan Ahmed
, Muhammad Faisal Iqbal
, Ayesha Rafiq

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

In this paper, a review of cone programming formulation of soft margin semi-supervised support vector machines is provided. The S 3 VM is known to be NP-hard, thus their cone programming reformulation remains NP-hard. However, the reformulation converts the problem into a convex optimization problem. The formulations can be classified into semidefinite programming reformulation and copositive reformulation. We have collected several semi-definite and copositive programming reformulations. The relations between these reformulations are also discussed.

Original language	English
Title of host publication	2019 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	978-1-5386-9509-8
DOIs	https://doi.org/10.1109/ICOMET.2019.8673478
Publication status	Published - 2019
Externally published	Yes

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10.1109/ICOMET.2019.8673478

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title = "On cone optimization approaches for semi-supervised support vector machines(S3VM)",

abstract = "In this paper, a review of cone programming formulation of soft margin semi-supervised support vector machines is provided. The S 3 VM is known to be NP-hard, thus their cone programming reformulation remains NP-hard. However, the reformulation converts the problem into a convex optimization problem. The formulations can be classified into semidefinite programming reformulation and copositive reformulation. We have collected several semi-definite and copositive programming reformulations. The relations between these reformulations are also discussed.",

author = "Faizan Ahmed and Iqbal, \{Muhammad Faisal\} and Ayesha Rafiq",

year = "2019",

doi = "10.1109/ICOMET.2019.8673478",

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On cone optimization approaches for semi-supervised support vector machines(S3VM). / Ahmed, Faizan; Iqbal, Muhammad Faisal; Rafiq, Ayesha.
2019 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019. IEEE, 2019.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - On cone optimization approaches for semi-supervised support vector machines(S3VM)

AU - Ahmed, Faizan

AU - Iqbal, Muhammad Faisal

AU - Rafiq, Ayesha

PY - 2019

Y1 - 2019

N2 - In this paper, a review of cone programming formulation of soft margin semi-supervised support vector machines is provided. The S 3 VM is known to be NP-hard, thus their cone programming reformulation remains NP-hard. However, the reformulation converts the problem into a convex optimization problem. The formulations can be classified into semidefinite programming reformulation and copositive reformulation. We have collected several semi-definite and copositive programming reformulations. The relations between these reformulations are also discussed.

AB - In this paper, a review of cone programming formulation of soft margin semi-supervised support vector machines is provided. The S 3 VM is known to be NP-hard, thus their cone programming reformulation remains NP-hard. However, the reformulation converts the problem into a convex optimization problem. The formulations can be classified into semidefinite programming reformulation and copositive reformulation. We have collected several semi-definite and copositive programming reformulations. The relations between these reformulations are also discussed.

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U2 - 10.1109/ICOMET.2019.8673478

DO - 10.1109/ICOMET.2019.8673478

M3 - Conference contribution

BT - 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019

PB - IEEE

ER -

On cone optimization approaches for semi-supervised support vector machines(S<sup>3</sup>VM)

Abstract

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