Trine Julie Abrahamsen

Ph.D.-stud., M.Sc.


I am a Ph.D. student at the Cognitive Systems (CogSys) group at the Institute of Informatics and Mathmatical Modelling (IMM), Technical University of Denmark (DTU).

The title of my PhD project is "Kernel Methods for machine learning with life science applications", and my supervisors are Professor Lars Kai Hansen, IMM, DTU and Associate Professor Ole Winther, IMM, DTU.

Publications

  • Rasmussen, Peter M., Abrahamsen, Trine J., Madsen, Kristoffer H., and Hansen, Lars K. (2012), Nonlinear Denoising and Analysis of Neuroimages with Kernel Principal Component Analysis and Pre-image Estimation, NeuroImage, Elsevier.

  • Abrahamsen, Trine J. and Hansen, Lars K. (2011), Restoring the Generalizability of SVM based Decoding in High Dimensional Neuroimage Data, NIPS-2011 Workshop on Machine Learning and Interpretation in Neuroimaging.

  • Abrahamsen, Trine J. and Hansen, Lars K. (2011), Sparse non-linear denoising: Generalization performance and pattern reproducibility in functional MRI, Pattern Recognition Letters, Elsevier, Volume 32, Issue 15, pp 2080-2085.

  • Hansen, Toke J., Abrahamsen, Trine J. and Hansen, Lars K. (2011), A Randomized Heuristic for Kernel Parameter Selection with Large-scale Multi-class Data, IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

  • Abrahamsen, Trine J. and Hansen, Lars K. (2011), A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis, Journal of Machine Learning Research, Vol 12, pp 2027-2044.

  • Abrahamsen, Trine J. and Hansen, Lars K. (2010), Sparse non-linear denoising of fMRI: Performance and pattern reproducibility, NIPS-2010 Workshop on Practical Applications of Sparse Modeling: Open Issues and New Directions.

  • Abrahamsen, Trine J. and Hansen, Lars K. (2010), Regularized Pre-image Estimation for Kernel PCA De-noising: Input Space Regularization and Sparse Reconstruction, Journal of Signal Processing Systems, Springer, Volume 65, Number 3, pp 403-412.

  • Abrahamsen, Trine J. and Hansen, Lars K. (2009), Input Space Regularization Stabilizes Pre-images for Kernel PCA De-noising, IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

  • Abrahamsen, Trine J. (2009), Kernel Methods for De-noising with Neuroimaging Application, Master's thesis.

    Bibtex entries of all publications.

    Talks

  • A Randomized Heuristic for Kernel Parameter Selection with Large-scale Multi-class Data, IEEE Workshop on Machine Learning for Signal Processing (MLSP 2011), September 2011, Beijing, China.    pdf

  • Kernel Methods for De-noising with Neuroimaging Application, Center for Integrated Molecular Brain Imaging (Cimbi), Semptember 2009, Rigshospitalet, Denmark.    ppt

  • Input Space Regularization Stabilizes Pre-images for Kernel PCA De-noising, IEEE Workshop on Machine Learning for Signal Processing (MLSP 2009), 2nd-4th September 2009, Grenoble, France.    ppt

  • Kernel Methods for De-noising with Neuroimaging Application, Master defence, August 2009, DTU, Denmark    ppt

    Misc

  • Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation    -    Examples and Matlab code

  • Sparse non-linear denoising of fMRI: Performance and pattern reproducibility    -    Movie: avi    Poster: pdf

    Curriculum Vitae

    Pdf version of CV:    pdf

    Contact

    Feel free to contact me if you are working in the same field, or if you for any other cause would like to discuss relevant topics with me.

    My e-mail adress is: tjab(at)remove-this.imm.dtu.dk

    My office phone number is: (+45) 45253888

    visitors: ,