To apply these results to time-varying convex optimization, we establish the strong infinitesimal contractivity of dynamics solving three canonical problems: monotone inclusions, linear ...

Abstract: In this paper, we devise a new convex optimization strategy to both reduce the peak-to-average power ratio (PAPR) and the PAPR variance of orthogonal frequency-division multiplexing (OFDM) ...

On the projected subgradient method for nonsmooth convex optimization in a Hilbert space, Mathematical Programming, 81 (1998), 23-37. [2] Bereznyev, V.A., Karmanov, V.G. and Tretyakov, A.A., The ...

For supplementary readings, with each lecture, we will have pointers to chapters from the following books: BV: Convex Optimization, Stephen Boyd and Lieven Vandenberghe, (available online for free).

In this paper, we study the nonconvex quadratic convex–concave minimax fractional optimization problem (P). First, based on the S-lemma and the convex Farkas lemma, we transform (P) into a generalized ...

Journal of Industrial and Management Optimization, 16(2), 835–856. Crossref, Web of Science, Google Scholar; Li, M, D Sun and K-C Toh (2016). A majorized ADMM with indefinite proximal terms for ...

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Convex optimization for java and scala, built on Apache Commons Math. ... The source code examples for the book "An Introduction to Optimization Algorithms" java local-search evolutionary-algorithm ...