Search Results for author: Gerrit J. J. van den Burg

Found 7 papers, 7 papers with code

On Memorization in Probabilistic Deep Generative Models

1 code implementation6 Jun 2021 Gerrit J. J. van den Burg, Christopher K. I. Williams

Recent advances in deep generative models have led to impressive results in a variety of application domains.

Density Estimation

An Evaluation of Change Point Detection Algorithms

3 code implementations13 Mar 2020 Gerrit J. J. van den Burg, Christopher K. I. Williams

Next, we present a benchmark study where 14 algorithms are evaluated on each of the time series in the data set.

Change Point Detection Time Series +1

Probabilistic sequential matrix factorization

1 code implementation9 Oct 2019 Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas, Mark F. J. Steel

In particular, we consider nonlinear Gaussian state-space models where sequential approximate inference results in the factorization of a data matrix into a dictionary and time-varying coefficients with potentially nonlinear Markovian dependencies.

Multivariate Time Series Forecasting Multivariate Time Series Imputation

Fast Meta-Learning for Adaptive Hierarchical Classifier Design

1 code implementation9 Nov 2017 Gerrit J. J. van den Burg, Alfred O. Hero

The proposed empirical estimates of the Bayes error rate are computed from the minimal spanning tree (MST) of the samples from each pair of classes.

Classification General Classification +1

SparseStep: Approximating the Counting Norm for Sparse Regularization

1 code implementation24 Jan 2017 Gerrit J. J. van den Burg, Patrick J. F. Groenen, Andreas Alfons

The SparseStep algorithm is presented for the estimation of a sparse parameter vector in the linear regression problem.

Sparse Learning Methodology 62J05, 62J07

GenSVM: A Generalized Multiclass Support Vector Machine

3 code implementations Journal of Machine Learning Research 2016 Gerrit J. J. van den Burg, Patrick J. F. Groenen

Traditional extensions of the binary support vector machine (SVM) to multiclass problems are either heuristics or require solving a large dual optimization problem.

Multi-class Classification

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