activity
20172023
most citedDuality in Multi-View Restricted Kernel Machines

1 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2023★ 1 cited

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…

cs.LG2023★ 1 cited

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…

cs.LG2020

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…

eess.SY2018

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…

eess.SY2018

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…

eess.SY2017

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…