Kristiaan Pelckmans

Orcid: 0000-0002-8486-0897

According to our database1, Kristiaan Pelckmans authored at least 67 papers between 2002 and 2024.

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Bibliography

2024
ASA - The Adaptive Scheduling Algorithm.
CoRR, 2024

2021
Detecting Suspicious Events in Fast Information Flows.
CoRR, 2021

A HPC Co-scheduler with Reinforcement Learning.
Proceedings of the Job Scheduling Strategies for Parallel Processing, 2021

2020
Monitoring High-Frequency Data Streams in FinTech: FADO Versus $K$K-Means.
IEEE Intell. Syst., 2020

Longitudinal Support Vector Machines for High Dimensional Time Series.
CoRR, 2020

APTER: Aggregated Prognosis Through Exponential Reweighting.
CoRR, 2020

ASA - The Adaptive Scheduling Architecture.
Proceedings of the HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

2019
Frequency conditions for stable networked controllers with time-delay.
Int. J. Control, 2019

APTER: Aggregated Prognosis Through Exponential Re-weighting.
Proceedings of the Computing and Combinatorics - 25th International Conference, 2019

2018
Worst-Case Prediction Performance Analysis of the Kalman Filter.
IEEE Trans. Autom. Control., 2018

A stability criterion for switching Lur'e systems with switching-path restrictions.
Autom., 2018

2017
FADO: A Deterministic Detection/Learning Algorithm.
CoRR, 2017

2016
A Direct Proof of the Discrete-Time Multivariate Circle and Tsypkin Criteria.
IEEE Trans. Autom. Control., 2016

2015
System components of a general theory of software engineering.
Sci. Comput. Program., 2015

Identifiability and convergence analysis of the MINLIP estimator.
Autom., 2015

On the nuclear norm heuristic for a Hankel matrix completion problem.
Autom., 2015

Conditions for input-output stability of discrete-time Lur'e systems with time-varying delays.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Stability analysis of an adaptively sampled controller for SISO systems with nonlinear feedback.
Proceedings of the American Control Conference, 2015

2014
On the Randomized Kaczmarz Algorithm.
IEEE Signal Process. Lett., 2014

Approximate adjoint-based iterative learning control.
Int. J. Control, 2014

Asymmetric v-tube support vector regression.
Comput. Stat. Data Anal., 2014

Sparse estimation from noisy observations of an overdetermined linear system.
Autom., 2014

2013
Randomized Gossip Algorithms for Achieving Consensus on the Majority Vote.
Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013

2012
On the Nuclear Norm heuristic for a Hankel matrix Recovery Problem
CoRR, 2012

An ellipsoid based, two-stage screening test for BPDN.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Sparse conjugate directions pursuit with application to fixed-size kernel models.
Mach. Learn., 2011

Learning Transformation Models for Ranking and Survival Analysis.
J. Mach. Learn. Res., 2011

Improved performance on high-dimensional survival data by application of Survival-SVM.
Bioinform., 2011

MINLIP for the identification of monotone Wiener systems.
Autom., 2011

Support vector methods for survival analysis: a comparison between ranking and regression approaches.
Artif. Intell. Medicine, 2011

A simple recursive algorithm for learning a Monotone Wiener system.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

An Adaptive Compression Algorithm in a Deterministic World.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2010
Linear Systems, Sparse Solutions, and Sudoku.
IEEE Signal Process. Lett., 2010

Efficient adaptive filtering for smooth linear FIR models.
Proceedings of the 18th European Signal Processing Conference, 2010

On the use of a clinical kernel in survival analysis.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Improved non-parametric sparse recovery with data matched penalties.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

On the identification of monotone Wiener systems.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009
Least conservative support and tolerance tubes.
IEEE Trans. Inf. Theory, 2009

Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes.
Proceedings of the Artificial Neural Networks, 2009

MINLIP: Efficient Learning of Transformation Models.
Proceedings of the Artificial Neural Networks, 2009

Transductively Learning from Positive Examples Only.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008
Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation.
Proceedings of the Artificial Neural Networks, 2008

Survival SVM: a practical scalable algorithm.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007
A Convex Approach to Validation-Based Learning of the Regularization Constant.
IEEE Trans. Neural Networks, 2007

Margin based Transductive Graph Cuts using Linear Programming.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Support and Quantile Tubes
CoRR, 2007

A Risk Minimization Principle for a Class of Parzen Estimators.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Transductive Rademacher Complexities for Learning Over a Graph.
Proceedings of the Mining and Learning with Graphs, 2007

Fixed-size kernel logistic regression for phoneme classification.
Proceedings of the INTERSPEECH 2007, 2007

Multi-class kernel logistic regression: a fixed-size implementation.
Proceedings of the International Joint Conference on Neural Networks, 2007

Convex optimization for the design of learning machines.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006
Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods.
Mach. Learn., 2006

2005
Subspace identification of Hammerstein systems using least squares support vector machines.
IEEE Trans. Autom. Control., 2005

Primal-Dual Monotone Kernel Regression.
Neural Process. Lett., 2005

Handling missing values in support vector machine classifiers.
Neural Networks, 2005

Building sparse representations and structure determination on LS-SVM substrates.
Neurocomputing, 2005

The differogram: Non-parametric noise variance estimation and its use for model selection.
Neurocomputing, 2005

Componentwise Least Squares Support Vector Machines
CoRR, 2005

Identification of MIMO Hammerstein models using least squares support vector machines.
Autom., 2005

Componentwise Support Vector Machines for Structure Detection.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

On Model Complexity Control in Identification of Hammerstein Systems.
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

Subspace intersection identification of Hammerstein-Wiener systems.
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

2004
Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Sparse LS-SVMs using additive regularization with a penalized validation criterion.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

2003
Variogram based noise variance estimation and its use in kernel based regression.
Proceedings of the NNSP 2003, 2003

2002
Robust Cross-Validation Score Function for Non-linear Function Estimation.
Proceedings of the Artificial Neural Networks, 2002


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