Bamdev Mishra

[+] CV

  • Low-rank factorizations for large-scale optimization algorithms:

    Here is my CV.

    The research deals with the application of manifold optimization techniques to large-scale convex optimization problems whose expected or desired solutions have low rank. We focus specifically on convex relaxations of large-scale rank-constrained problems encountered in machine learning, data reduction and bioinformatics.

    As of now, I am trying to understand this comic strip.


[+] Education and research experience

[+] Publications and codes



[+] Teaching and graduate courses

  • 2012 Sem 1: SYST003 Lab (Teaching Assistant)
  • 2011 Sem 2: Numerical Optimization (Teaching Assistant): Tutorials
  • 2011 Sem 1: Theory of Computation
  • INRIA/ENS: 2011 July: CVML Summer school
  • EECI: 2011 Feb: Optimization on Matrix Manifolds
  • SOCN: 2010 Dec: Compressed Sensing and Sparse Approximations
  • Sys017: 2010 Sem 1: Nonlinear Systems


[+] Activities

  • Actively involved in the open-source MATLAB toolbox Manopt for optimization on matrix manifold
  • Teaching assistant at ULg
  • Created and maintained the research unit website Systmod from September 2011 to December 2013


[+] Recent updates

  • startag The technical report and the Matlab codes for "A Riemannian approach to low-rank algebraic Riccati equations" [arXiv:1312.4883][Matlab code] are online.

  • startagR3MC: A Riemannian three-factor algorithm for low-rank matrix completion [arXiv:1306.2672][Matlab code] is now online. Here we show some promising results of employing the Riemannian preconditioning appoach on the low-rank manifold. More on this to follow soon...

  • startag The paper [arXiv:1308.5200] on the Manopt toolbox is now available online.

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