Kristiaan Pelckmans

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 14

Top Topics

Noisy Observations

Scheduling Algorithm

Information Flow

Top Venues

Int. J. Control

IEEE Trans. Autom. Control.

Publications

Abel Souza, Kristiaan Pelckmans, Johan Tordsson
A HPC Co-Scheduler with Reinforcement Learning. CoRR (2024)
Abel Souza, Kristiaan Pelckmans, Devarshi Ghoshal, Lavanya Ramakrishnan, Johan Tordsson
ASA - The Adaptive Scheduling Algorithm. CoRR (2024)
Kristiaan Pelckmans, Moustafa Aboushady, Andreas Brosemyr
Detecting Suspicious Events in Fast Information Flows. CoRR (2021)
Abel Souza, Kristiaan Pelckmans, Johan Tordsson
A HPC Co-scheduler with Reinforcement Learning. JSSPP (2021)
Kristiaan Pelckmans, Hong-Li Zeng
Longitudinal Support Vector Machines for High Dimensional Time Series. CoRR (2020)
Kristiaan Pelckmans, Liu Yang
APTER: Aggregated Prognosis Through Exponential Reweighting. CoRR (2020)
Abel Souza, Kristiaan Pelckmans, Devarshi Ghoshal, Lavanya Ramakrishnan, Johan Tordsson
ASA - The Adaptive Scheduling Architecture. HPDC (2020)
Kristiaan Pelckmans
Monitoring High-Frequency Data Streams in FinTech: FADO Versus $K$K-Means. IEEE Intell. Syst. 35 (2) (2020)
Yang Liu, Kristiaan Pelckmans
APTER: Aggregated Prognosis Through Exponential Re-weighting. COCOON (2019)
Johannes Nygren, Torbjörn Wigren, Kristiaan Pelckmans
Frequency conditions for stable networked controllers with time-delay. Int. J. Control 92 (4) (2019)
Johannes Nygren, Kristiaan Pelckmans
A stability criterion for switching Lur'e systems with switching-path restrictions. Autom. 96 (2018)
Sholeh Yasini, Kristiaan Pelckmans
Worst-Case Prediction Performance Analysis of the Kalman Filter. IEEE Trans. Autom. Control. 63 (6) (2018)
Kristiaan Pelckmans
FADO: A Deterministic Detection/Learning Algorithm. CoRR (2017)
Johannes Nygren, Kristiaan Pelckmans
A Direct Proof of the Discrete-Time Multivariate Circle and Tsypkin Criteria. IEEE Trans. Autom. Control. 61 (2) (2016)
Johannes Nygren, Kristiaan Pelckmans
Stability analysis of an adaptively sampled controller for SISO systems with nonlinear feedback. ACC (2015)
Anca-Juliana Stoica, Kristiaan Pelckmans, William Rowe
System components of a general theory of software engineering. Sci. Comput. Program. 101 (2015)
Liang Dai, Kristiaan Pelckmans, Er-Wei Bai
Identifiability and convergence analysis of the MINLIP estimator. Autom. 51 (2015)
Johannes Nygren, Kristiaan Pelckmans
Conditions for input-output stability of discrete-time Lur'e systems with time-varying delays. CDC (2015)
Liang Dai, Kristiaan Pelckmans
On the nuclear norm heuristic for a Hankel matrix completion problem. Autom. 51 (2015)
Johannes Nygren, Kristiaan Pelckmans, Bengt Carlsson
Approximate adjoint-based iterative learning control. Int. J. Control 87 (5) (2014)
Liang Dai, Mojtaba Soltanalian, Kristiaan Pelckmans
On the Randomized Kaczmarz Algorithm. IEEE Signal Process. Lett. 21 (3) (2014)
Liang Dai, Mojtaba Soltanalian, Kristiaan Pelckmans
On the Randomized Kaczmarz Algorithm. CoRR (2014)
Xiaolin Huang, Lei Shi, Kristiaan Pelckmans, Johan A. K. Suykens
Asymmetric v-tube support vector regression. Comput. Stat. Data Anal. 77 (2014)
Liang Dai, Kristiaan Pelckmans
Sparse Estimation From Noisy Observations of an Overdetermined Linear System. CoRR (2014)
Liang Dai, Kristiaan Pelckmans
Sparse estimation from noisy observations of an overdetermined linear system. Autom. 50 (11) (2014)
Kristiaan Pelckmans
Randomized Gossip Algorithms for Achieving Consensus on the Majority Vote. ALCOSP (2013)
Liang Dai, Kristiaan Pelckmans
On the Nuclear Norm heuristic for a Hankel matrix Recovery Problem CoRR (2012)
Liang Dai, Kristiaan Pelckmans
An ellipsoid based, two-stage screening test for BPDN. EUSIPCO (2012)
Kristiaan Pelckmans, Liang Dai
A simple recursive algorithm for learning a Monotone Wiener system. CDC/ECC (2011)
Kristiaan Pelckmans
An Adaptive Compression Algorithm in a Deterministic World. Algorithmic Probability and Friends (2011)
Kristiaan Pelckmans
MINLIP for the identification of monotone Wiener systems. Autom. 47 (10) (2011)
Peter Karsmakers, Kristiaan Pelckmans, Kris De Brabanter, Hugo Van hamme, Johan A. K. Suykens
Sparse conjugate directions pursuit with application to fixed-size kernel models. Mach. Learn. 85 (1-2) (2011)
Vanya Van Belle, Kristiaan Pelckmans, Sabine Van Huffel, Johan A. K. Suykens
Improved performance on high-dimensional survival data by application of Survival-SVM. Bioinform. 27 (1) (2011)
Vanya Van Belle, Kristiaan Pelckmans, Sabine Van Huffel, Johan A. K. Suykens
Support vector methods for survival analysis: a comparison between ranking and regression approaches. Artif. Intell. Medicine 53 (2) (2011)
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel
Learning Transformation Models for Ranking and Survival Analysis. J. Mach. Learn. Res. 12 (2011)
Kristiaan Pelckmans, Toon van Waterschoot, Johan A. K. Suykens
Efficient adaptive filtering for smooth linear FIR models. EUSIPCO (2010)
Prabhu Babu, Kristiaan Pelckmans, Petre Stoica, Jian Li
Linear Systems, Sparse Solutions, and Sudoku. IEEE Signal Process. Lett. 17 (1) (2010)
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel
On the use of a clinical kernel in survival analysis. ESANN (2010)
Kristiaan Pelckmans
On the identification of monotone Wiener systems. CDC (2010)
Kristiaan Pelckmans
MINLIP for the Identification of Monotone Wiener Systems CoRR (2010)
Marco Signoretto, Kristiaan Pelckmans, Lieven De Lathauwer, Johan A. K. Suykens
Improved non-parametric sparse recovery with data matched penalties. CIP (2010)
Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. ICANN (1) (2009)
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel
MINLIP: Efficient Learning of Transformation Models. ICANN (1) (2009)
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel
Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints. IWANN (1) (2009)
Kristiaan Pelckmans, Johan A. K. Suykens
Transductively Learning from Positive Examples Only. ESANN (2009)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Least conservative support and tolerance tubes. IEEE Trans. Inf. Theory 55 (8) (2009)
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel
Survival SVM: a practical scalable algorithm. ESANN (2008)
Marco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens
Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation. ICANN (1) (2008)
Kristiaan Pelckmans, John Shawe-Taylor, Johan A. K. Suykens, Bart De Moor
Margin based Transductive Graph Cuts using Linear Programming. AISTATS (2007)
Kristiaan Pelckmans, Johan A. K. Suykens
Transductive Rademacher Complexities for Learning Over a Graph. MLG (2007)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Convex optimization for the design of learning machines. ESANN (2007)
Peter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens, Hugo Van hamme
Fixed-size kernel logistic regression for phoneme classification. INTERSPEECH (2007)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
A Convex Approach to Validation-Based Learning of the Regularization Constant. IEEE Trans. Neural Networks 18 (3) (2007)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Support and Quantile Tubes CoRR (2007)
Peter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens
Multi-class kernel logistic regression: a fixed-size implementation. IJCNN (2007)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
A Risk Minimization Principle for a Class of Parzen Estimators. NIPS (2007)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods. Mach. Learn. 62 (3) (2006)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
The differogram: Non-parametric noise variance estimation and its use for model selection. Neurocomputing 69 (1-3) (2005)
Kristiaan Pelckmans, Johan A. K. Suykens, Ivan Goethals, Bart De Moor
On Model Complexity Control in Identification of Hammerstein Systems. CDC/ECC (2005)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Handling missing values in support vector machine classifiers. Neural Networks 18 (5-6) (2005)
Kristiaan Pelckmans, Marcelo Espinoza, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Primal-Dual Monotone Kernel Regression. Neural Process. Lett. 22 (2) (2005)
Ivan Goethals, Kristiaan Pelckmans, Luc Hoegaerts, Johan A. K. Suykens, Bart De Moor
Subspace intersection identification of Hammerstein-Wiener systems. CDC/ECC (2005)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Componentwise Support Vector Machines for Structure Detection. ICANN (2) (2005)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Building sparse representations and structure determination on LS-SVM substrates. Neurocomputing 64 (2005)
Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Identification of MIMO Hammerstein models using least squares support vector machines. Autom. 41 (7) (2005)
Kristiaan Pelckmans, Ivan Goethals, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Componentwise Least Squares Support Vector Machines CoRR (2005)
Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Subspace identification of Hammerstein systems using least squares support vector machines. IEEE Trans. Autom. Control. 50 (10) (2005)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs. ICONIP (2004)
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor
Sparse LS-SVMs using additive regularization with a penalized validation criterion. ESANN (2004)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Variogram based noise variance estimation and its use in kernel based regression. NNSP (2003)
Jos De Brabanter, Kristiaan Pelckmans, Johan A. K. Suykens, Joos Vandewalle
Robust Cross-Validation Score Function for Non-linear Function Estimation. ICANN (2002)