scholarly journals Globally solving quadratic programs with convex objective and complementarity constraints via completely positive programming

2018 ◽  
Vol 14 (2) ◽  
pp. 625-636
Author(s):  
Zhi-Bin Deng ◽  
◽  
Ye Tian ◽  
Cheng Lu ◽  
Wen-Xun Xing ◽  
...  
Keyword(s):  
Complementarity Constraints ◽  
Quadratic Programs ◽  
Completely Positive ◽  
Completely Positive Programming

The C-Index: A New Stability Concept for Quadratic Programs with Complementarity Constraints

2011 ◽  
Vol 36 (3) ◽  
pp. 504-526 ◽  
Author(s):  
Daniel Ralph ◽  
Oliver Stein
Keyword(s):  
Complementarity Constraints ◽  
Quadratic Programs ◽  
Stability Concept

Modularity maximization using completely positive programming

2017 ◽  
Vol 471 ◽  
pp. 20-32 ◽  
Author(s):  
Sakineh Yazdanparast ◽  
Timothy C. Havens
Keyword(s):  
Completely Positive ◽  
Modularity Maximization ◽  
Completely Positive Programming

scholarly journals A New Conic Approach to Semisupervised Support Vector Machines

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ye Tian ◽  
Jian Luo ◽  
Xin Yan
Keyword(s):  
Quadratic Forms ◽  
Optimal Solution ◽  
Positive Cone ◽  
Support Vector ◽  
Completely Positive ◽  
Adaptive Scheme ◽  
Completely Positive Cone ◽  
Vector Machines ◽  
Programming Techniques ◽  
Completely Positive Programming

We propose a completely positive programming reformulation of the 2-norm soft marginS3VMmodel. Then, we construct a sequence of computable cones of nonnegative quadratic forms over a union of second-order cones to approximate the underlying completely positive cone. Anϵ-optimal solution can be found in finite iterations using semidefinite programming techniques by our method. Moreover, in order to obtain a good lower bound efficiently, an adaptive scheme is adopted in our approximation algorithm. The numerical results show that the proposed algorithm can achieve more accurate classifications than other well-known conic relaxations of semisupervised support vector machine models in the literature.

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