Dr. Kris De Brabanter | OPTEC - K.U.Leuven CoE Optimization in Engineering

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Dr. Kris De Brabanter (ESAT)

My K.U.Leuven Curriculum Vitae

Member of:

Data-driven modelling (WG2)
Parameter and State Estimation (WG3)

IT (Articles in internationally reviewed academic journals)

De Brabanter, K., Karsmakers, P., De Brabanter, J., Suykens, J., De Moor, B. (2012). Confidence bands for least squares support vector machine classifiers : a regression approach. Pattern Recognition, 45 (6), 2280-2287.

Sahhaf, S., Degraeve, R., Srividya, V., De Brabanter, K., Schram, T., Gilbert, M., Vandervorst, W., Groeseneken, G. (2012). HfSiO Bulk Trap Density Controls the Initial Vth in nMOSFETs. IEEE Transactions on Device and Materials Reliability, accepted.

Falck, T., Dreesen, P., De Brabanter, K., Pelckmans, K., De Moor, B., Suykens, J. (2012). Least-Squares Support Vector Machines for the Identification of Wiener-Hammerstein Systems. Control Engineering Practice, accepted.

Sahhaf, S., De Brabanter, K., Degraeve, R., Suykens, J., De Moor, B., Groeseneken, G. (2012). Modelling of charge trapping/De-trapping induced voltage instability in high-k Gate dielectrics. IEEE Transactions on Device and Materials Reliability, 12 (1), 152-157.

De Brabanter, K., De Brabanter, J., Suykens, J., De Moor, B. (2011). Approximate confidence and prediction intervals for least squares support vector regression. IEEE Transactions on Neural Networks, 22 (1), 110-120.

De Brabanter, K., De Brabanter, J., Suykens, J., De Moor, B. (2011). Kernel regression in the presence of correlated errors. Journal of Machine Learning Research, 12, 1955-1976.

Karsmakers, P., Pelckmans, K., De Brabanter, K., Van hamme, H., Suykens, J. (2011). Sparse conjugate directions pursuit with application to fixed-size Kernel models. Machine Learning, 85 (1-2), 109-148.

De Brabanter, K., De Brabanter, J., Suykens, J., De Moor, B. (2010). Optimized Fixed-Size Kernel Models for Large Data Sets. Computational Statistics & Data Analysis, 54 (6), 1484-1504.

Sahhaf, S., Degraeve, R., Cho, M., De Brabanter, K., Roussel, P., Zahid, M., Groeseneken, G. (2010). Detailed analysis of charge pumping and ldVg Hysteresis for profiling traps in SiO2/HfSiO(N). Microelectronic Engineering, 87 (10), 2614-2619.

IC (Papers at international scientific conferences and symposia, published in full in proceedings)

De Brabanter, K., De Moor, B. (2012). Deconvolution in nonparametric statistics. Proc. of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Brugge, Belgium, Apr. 2012 (pp. 341-350).

De Brabanter, K., De Brabanter, J., Suykens, J., Vandewalle, J., De Moor, B. (2012). Robustness of Kernel Based Regression : Influence and Weight Functions. Proc. of the International Joint Conference on Neural Networks (IJCNN 2012): Vol. a. International Joint Conference on Neural Networks (IJCNN 2012), 2012.

De Brabanter, K., De Brabanter, J., Gijbels, I., Suykens, J., De Moor, B. (2011). New developments in Kernel regression with correlated errors. Graybill 2011 conference on Modern Nonparametric Methods (Graybill). Graybill 2011 conference on Modern Nonparametric Methods (Graybill). Fort Collins, Colorado, Jun. 2011.

Garcia Lopez, J., De Brabanter, K., Dorronsoro, J., Suykens, J. (2011). Sparse LS-SVMs with L0-Norm Minimization. Proc. of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Brugge, Belgium, Apr., 2011 (pp. 189-194).

Huyck, B., De Brabanter, K., Logist, F., De Brabanter, J., Van Impe, J., De Moor, B. (2011). Identification of a pilot scale distillation column : A kernel based approach. In Bittanti, S. (Ed.), Cenedese, A. (Ed.), Zampieri, S. (Ed.), Proc. of the 18th World Congress of the International Federation of Automatic Control (IFAC). IFAC World Congress 2011. Milan, Italy, 28 August-02 September 2011 (pp. 471-476).

De Brabanter, K., Sahhaf, S., Karsmakers, P., De Brabanter, J., Suykens, J., De Moor, B. (2010). Nonparametric comparison of densities based on statistical bootstrap. Proc. of the 4th European Conference on the Use of Modern Information and Communication Technologies (ECUMICT 2010). 4th European Conference on the Use of Modern Information and Communication Technologies (ECUMICT 2010). Gent, Belgium, Mar. 2010 (pp. 179-190).

De Brabanter, K., Karsmakers, P., De Brabanter, J., Pelckmans, K., Suykens, J., De Moor, B. (2010). On robustness in Kernel based regression. Proc. of NIPS 2010 Workshop Robust Statistical Learning (ROBUSTML) (NIPS 2010). NIPS 2010 Workshop Robust Statistical Learning (ROBUSTML). Whistler, Canada, Dec. 2010.

De Brabanter, K., De Brabanter, J., Suykens, J., De Moor, B. (2010). Kernel regression with correlated errors. Proc. of the 11th International Symposium on Computer Applications in Biotechnology (CAB). 11th International Symposium on Computer Applications in Biotechnology (CAB). Leuven, Belgium, Jul. 2010 (pp. 13-18).

De Brabanter, K., Pelckmans, K., De Brabanter, J., Debruyne, M., Suykens, J., Hubert, M., De Moor, B. (2009). Robustness of Kernel Based Regression: a Comparison of Iterative Weighting Schemes. Proc. of the 19th International Conference on Artificial Neural Networks (ICANN). 19th International Conference on Artificial Neural Networks (ICANN). Limassol, Cyprus, Sep. 2009 (pp. 100-110).

De Brabanter, K., Dreesen, P., Karsmakers, P., Pelckmans, K., De Brabanter, J., Suykens, J., De Moor, B. (2009). Fixed-size LS-SVM applied to the Wiener-Hammerstein Benchmark. Proc. of the 15th IFAC symposium on System Identification (SYSID 2009). 15th IFAC symposium on System Identification (SYSID 2009). Saint-Malo, France, Jul. 2009 (pp. 826-831).

AC (Papers at other scientific conferences and symposia, published in full in proceedings)

De Brabanter, K., De Brabanter, J., De Moor, B. (2011). Nonparametric derivative estimation. Proc. of the 23rd Benelux Conference on Artificial Intelligence. 23rd Benelux Conference on Artificial Intelligence. Gent, Belgium, Nov. 2011 (pp. 75-81).

AMa (Meeting abstracts, presented at other scientific conferences and symposia, published or not published in proceedings or journals)

Huyck, B., De Brabanter, K., Logist, F., De Brabanter, J., Van Impe, J., De Moor, B. (2011). LS-SVM Identification of a Distillation Column. Benelux Meeting on Systems and Control. Lommel, Belgium, 15-17 March 2011.

TH (Thesis)

De Brabanter, K., De Moor, B. (sup.), Suykens, J. (sup.) (2011). Least Squares Support Vector Regression with Applications to Large-Scale Data: a Statistical Approach (Kleinste kwadraten support vector regressie met toepassingen op grote datasets: een statistische benadering), 246 pp.

This list is generated from Lirias and contains data from Lirias as it is entered and validated by the researcher.

Newsflash

Two OPTEC professors have been awarded three "Gouden Krijtjes", the yearly teaching awards given by the organization of engineering students (vtk). Prof. Lombaert was awarded the prize for the best course in civil engineering, and Prof. Diehl the prizes for the best professor and the best course in mathematical engineering (where he teaches numerical optimization). They received these awards at the yearly "proffentap" where experienced students taught them how to draft beer professionally.