- Title
- Symbolic computation of multidimensional Fenchel conjugates
- Creator
- Borwein, Jonathan M.; Hamilton, Chris H.
- Relation
- 2006 International Symposium on Symbolic and Algebraic Computations (ISSAC '06). Proceedings of the 2006 International Symposium on Symbolic and Algebraic Computations (Genova, Italy 9-12 July, 2006) p. 23-30
- Publisher Link
- http://dx.doi.org/10.1145/1145768.1145780
- Publisher
- Association for Computing Machinery
- Resource Type
- conference paper
- Date
- 2006
- Description
- Convex optimization is a branch of mathematics dealing with non-linear optimization problems with additional geometric structure. This area has been the focus of considerable recent research due to the fact that convex optimization problems are scalable and can be efficiently solved by interior-point methods. Over the last ten years or so, convex optimization has found new applications in many areas including control theory, signal processing, communications and networks, circuit design, data analysis and finance.Of key importance in convex optimization is the notion of duality, and in particular that of Fenchel duality. This work explores algorithms for calculating symbolic Fenchel conjugates of a class of real-valued functions defined on ℝn, extending earlier work to the non-separable multi-dimensional case. It also explores the potential application of the developed algorithms to automatic inequality proving.
- Subject
- Fenchel conjugate; Legendre Fenchel transform; subdifferential; subgradient; inequalities; computer proofs
- Identifier
- http://hdl.handle.net/1959.13/1038456
- Identifier
- uon:13545
- Identifier
- ISBN:9781595932761
- Rights
- © ACM, 2006. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 2006 International Symposium on Symbolic and Algebraic Computations {ISSAC '06} http://doi.acm.org/10.1145/1145768.1145780
- Language
- eng
- Full Text
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