342 citations · 638 across the 10 of their papers we have counts for
14 papers
Porteous Meets Walsh: Counting Critical Points for -Norm Model Order Reduction Using Algebraic Geometry Behind Multiparameter Eigenvalue Problems
Sibren Lagauw, Leonie Kayser, Bart De Moor
Several polynomial systems arising in systems and control have been shown to exhibit a partially linear structure, which allows them to be reformulated as a multiparameter eigenval…
Duality in Multi-View Restricted Kernel Machines
Sonny Achten, Arun Pandey, Hannes De Meulemeester +2
We propose a unifying setting that combines existing restricted kernel machine methods into a single primal-dual multi-view framework for kernel principal component analysis in bot…
Multi-view Kernel PCA for Time series Forecasting
Arun Pandey, Hannes De Meulemeester, Bart De Moor +1
In this paper, we propose a kernel principal component analysis model for multi-variate time series forecasting, where the training and prediction schemes are derived from the mult…
The Bures Metric for Generative Adversarial Networks
Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel +2
Generative Adversarial Networks (GANs) are performant generative methods yielding high-quality samples. However, under certain circumstances, the training of GANs can lead to mode…
Applicability and interpretation of the deterministic weighted cepstral distance
Oliver Lauwers, Bart De Moor
Quantifying similarity between data objects is an important part of modern data science. Deciding what similarity measure to use is very application dependent. In this paper, we co…
A Multiple-Input Multiple-Output Cepstrum
Oliver Lauwers, Oscar Mauricio Agudelo, Bart De Moor
This paper extends the concept of scalar cepstrum coefficients from single-input single-output linear time invariant dynamical systems to multiple-input multiple-output models, mak…
A time series distance measure for efficient clustering of input output signals by their underlying dynamics
Oliver Lauwers, Bart De Moor
Starting from a dataset with input/output time series generated by multiple deterministic linear dynamical systems, this paper tackles the problem of automatically clustering these…
Assessing binary classifiers using only positive and unlabeled data
Marc Claesen, Jesse Davis, Frank De Smet +1
Assessing the performance of a learned model is a crucial part of machine learning. However, in some domains only positive and unlabeled examples are available, which prohibits the…
Hyperparameter Search in Machine Learning
Marc Claesen, Bart De Moor
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt t…
Easy Hyperparameter Search Using Optunity
Marc Claesen, Jaak Simm, Dusan Popovic +2
Optunity is a free software package dedicated to hyperparameter optimization. It contains various types of solvers, ranging from undirected methods to direct search, particle swarm…
EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines
Marc Claesen, Frank De Smet, Johan Suykens +1
EnsembleSVM is a free software package containing efficient routines to perform ensemble learning with support vector machine (SVM) base models. It currently offers ensemble method…
Fast Prediction with SVM Models Containing RBF Kernels
Marc Claesen, Frank De Smet, Johan A. K. Suykens +1
We present an approximation scheme for support vector machine models that use an RBF kernel. A second-order Maclaurin series approximation is used for exponentials of inner product…
A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models
Marc Claesen, Frank De Smet, Johan A. K. Suykens +1
We present a novel approach to learn binary classifiers when only positive and unlabeled instances are available (PU learning). This problem is routinely cast as a supervised task…
On the maximum rank of Toeplitz block matrices of blocks of a given pattern
Gunther Reißig
We show that the maximum rank of block lower triangular Toeplitz block matrices equals their term rank if the blocks fulfill a structural condition, i.e., only the locations but no…