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This is a sample blog post. Blog posts are cool.
Code for Euclidean Distance Matrix Completion
RPCA using a facial reduction model
Citation: Ming-Wen Chen, XIn-Feng Wang, Fei Wang, Guo-biao Lin, Zi-Zong Wang. (2013). " The effect of interfacial kinetics on the morphological stability of a spherical particle. " Journal of Crystal Growth. 362(1), Pages 20-23.
Citation: Greg Reid, Fei Wang, Wenyuan Wu. (2014). " A note on geometric involutive bases for positive dimensional polynomial ideals and SDP methods. " Proceedings of the 2014 Symposium on Symbolic-Numeric Computation. Pages 41-42.
Citation: Robert Corless, David Jeffrey, Fei Wang. (2014). " The asymptotic analysis of some interrpolated nonlinear recurrence relations. " Proceedings of the 39th International Symposium on Symbolic and Algebraic Computation. Pages 115-121.
Citation: Fei Wang. (2016). " Proof of a serie's solution for Eulers trinomial equation. " ACM Communications in Computer Algebra. 50(4), Pages 136-144.
Citation: Fei Wang, Greg Reid, Henry Wolkowicz. (2017). " An SDP-based method for the real radical ideal membership test. " 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. Pages 86-93.
Citation: Stefan Sremac, Fei Wang, Henry Wolkowicz, Lucas Petterson. (2019). " Noisy Euclidean Distance Matrix Completion with a Single Missing Node." Journal of Global Optimization. 75(4), Pages 973-1002
Citation: Marcia Fampa, Daniela Luke, Fei Wang, Henry Wolkowicz. (2020). " Parametric Convex Quadratic Relaxational of the Quadratic Knapsack Problem. " European Journal of Operational Research. 281(1), Pages 36-49.
Citation: Shiqian Ma, Fei Wang, Linchuan Wei, Henry Wolkowicz. (2020). " Robust Principal Component Analysis using Facial Reduction. " Optimization and Engineering. 21(3), Pages 1195-1219.
Citation: Anders Forsgren, Fei Wang. (2020). " On the existence of a short pivoting sequence for a linear program." Operational Research Letters. 48(6), Pages 697-702.
Citation: Fei Wang, Henry Wolkowicz. (2022). " Singularite degree of non-facially exposed faces." 10.48550/ARXIV.2211.00834v2.
Citation: Fei Wang. (2022). " Uniqueness of Low Rank Matrix Completion and Schur Complement." 10.48550/ARXIV.2206.15018.
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In 1779, Leonhard Euler published a paper about Lambert’s transcendental equation in the symmetric form. In the paper, he studied the series solution of this equation and other results based on an assumption which was not proved in the paper. Euler’s paper gave the first series expanion for the so-called Lambert W function. In this work, we briefly review Euler’s results and give a proof to modern standards of rigor of the series solution of Lambert’s transcendental equation.
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2016 CMS Winter Meeting Large Scale Optimization: Theory, Algorithms and Applications in memoriam Jonathan Borwein
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SYNASC 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.
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ISMP 2018 the 23rd International Symposium on Mathematical Programming.
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ICCOPT 2019 the 6th International Coneference on Continuous Optimization.
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Graduate Course on Real algebraic & Distance geometry in Discrete Structures and Kinematics
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Abstract: We define the singularity degree of a face which is not necessarily facially exposed. We show that the singularity degree of a linear conic optimization problem is equal to the singularity degree of the minimal face on the linear image of the convex cone, which generalises the result by Drusvyatskiy, Pataki and Wolkowicz in 2015. Given pairwise distances of a framework (G, p), the singularity degree of the corresponding EDM completion problem is related to the stability of the framework (high singularity means the framework is less stable). As an application, we give an upper bound of the singularity degree for generic frameworks and tensegrities underlying a Laman plus d graph ( Laman graph plus d edges).
Undergraduate course, University of Waterloo, 2020
Course Description: This is a course on linear algebra and its applications to engineering. Topics to be covered include complex numbers; vectors, lines and planes; systems of linear equations; matrices, linear transformations and determinants; introduction to vector spaces; eigenvalues, eigenvectors and diagonaliza- tion; and additional topics as time permits. We approach the material through a blend of theoretical ideas, computational methods and some applications.
Undergraduate course, Department of Combinatorics and Optimization, University of Waterloo, 2021
An introductory course to the mathematics of nonlinear optimization. Necessary and sufficient optimality conditions for unconstrained and constrained problems. Convexity and its applications. Computational algorithms and their analysis. Application to machine learning.
Undergraduate course, University of Waterloo, Department of Combinatorics and Optimization, 2022
This is an introductory course to linear programming, integer programming, and a very basic introduction to nonlinear optimization