Rachael Tappenden

LecturerRachael Tappenden

Erskine 714
Internal Phone: 92437

Qualifications

Research Interests

My research interests lie in the broad area of optimization and numerical linear algebra.

Recent Publications

  • Robinson DP. and Tappenden R. (2017) A Flexible ADMM Algorithm for Big Data Applications. Journal of Scientific Computing 71(1): 435-467. http://dx.doi.org/10.1007/s10915-016-0306-6.
  • Ma C., Tappenden R. and Takac M. (2016) Linear convergence of randomized feasible descent methods under the weak strong convexity assumption. Journal of Machine Learning Research 17: 1-24.
  • Tappenden R., Richtarik P. and Gondzio J. (2016) Inexact Coordinate Descent: Complexity and Preconditioning. Journal of Optimization Theory and Applications (early access online) http://link.springer.com/article/10.1007/s10957-016-0867-4.
  • Tappenden R., Richtárik P. and Büke B. (2015) Separable approximations and decomposition methods for the augmented Lagrangian. Optimization Methods and Software 30(3): 643-668. http://dx.doi.org/10.1080/10556788.2014.966824.
  • Tappenden R., Hegarty J., Broughton R., Butler A., Coope I. and Renaud P. (2013) X-ray image enhancement via determinant based feature selection. Australasian Physical & Engineering Sciences in Medicine 36(4): 449-455. http://link.springer.com/article/10.1007/s13246-013-0221-1.