Zoltán Szabó

Pierre-Cyril Aubin-Frankowski

J. Mach. Learn. Res., 2022

Discussion of 'Multiscale Fisher's Independence Test for Multivariate Dependence'.

[BibT_eX]

[DOI]

CoRR, 2022

2020

Hard Shape-Constrained Kernel Machines.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On Kernel Derivative Approximation with Random Fourier Features.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017

Characteristic and Universal Tensor Product Kernels.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

A Linear-Time Kernel Goodness-of-Fit Test.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

An Adaptive Test of Independence with Analytic Kernel Embeddings.

[BibT_eX]

[DOI]

Wittawat Jitkrittum

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Learning Theory for Distribution Regression.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Interpretable Distribution Features with Maximum Testing Power.

[BibT_eX]

[DOI]

Wittawat Jitkrittum

Kacper P. Chwialkowski

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

[BibT_eX]

[DOI]

Balaji Lakshminarayanan

Dino Sejdinovic

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal Rates for Random Fourier Features.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM).

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Two-stage sampled learning theory on distributions.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Information theoretical estimators toolbox.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2014

Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding.

[BibT_eX]

[DOI]

CoRR, 2014

Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2014, 2014

2013

Explaining Unintelligible Words by Means of their Context.

[BibT_eX]

Proceedings of the ICPRAM 2013, 2013

Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition Applications and Methods - International Conference, 2013

Emotional Expression Classification Using Time-Series Kernels.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

Separation theorem for independent subspace analysis and its consequences.

[BibT_eX]

[DOI]

Pattern Recognit., 2012

3D shape estimation in video sequences provides high precision evaluation of facial expressions.

[BibT_eX]

[DOI]

Image Vis. Comput., 2012

Distributed high dimensional information theoretical image registration via random projections.

[BibT_eX]

[DOI]

Digit. Signal Process., 2012

Automated Word Puzzle Generation via Topic Dictionaries

[BibT_eX]

[DOI]

CoRR, 2012

Collaborative Filtering via Group-Structured Dictionary Learning.

[BibT_eX]

[DOI]

Proceedings of the Latent Variable Analysis and Signal Separation, 2012

2011

Nonparametric independent process analysis.

[BibT_eX]

[DOI]

Proceedings of the 19th European Signal Processing Conference, 2011

Nonparametric divergence estimators for independent subspace analysis.

[BibT_eX]

[DOI]

Jeff G. Schneider

Proceedings of the 19th European Signal Processing Conference, 2011

Online group-structured dictionary learning.

[BibT_eX]

[DOI]

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Auto-regressive independent process analysis without combinatorial efforts.

[BibT_eX]

[DOI]

Pattern Anal. Appl., 2010

Towards Nonstationary, Nonparametric Independent Process Analysis with Unknown Source Component Dimensions

[BibT_eX]

[DOI]

CoRR, 2010

Autoregressive independent process analysis with missing observations.

[BibT_eX]

[DOI]

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2009

Separation Principles in Independent Process Analysis

[BibT_eX]

[DOI]

PhD thesis, 2009

Complex Independent Process Analysis.

[BibT_eX]

[DOI]

Acta Cybern., 2009

Controlled Complete ARMA Independent Process Analysis.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2009

Fast Parallel Estimation of High Dimensional Information Theoretical Quantities with Low Dimensional Random Projection Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Independent Component Analysis and Signal Separation, 2009

Complete Blind Subspace Deconvolution.

[BibT_eX]

[DOI]

Proceedings of the Independent Component Analysis and Signal Separation, 2009

2007

Undercomplete Blind Subspace Deconvolution.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2007

Neurally plausible, non-combinatorial iterative independent process analysis.

[BibT_eX]

[DOI]

Neurocomputing, 2007

Independent Subspace Analysis can Cope with the 'Curse of Dimensionality'.

[BibT_eX]

[DOI]

Acta Cybern., 2007

Post Nonlinear Independent Subspace Analysis.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2007

Independent Process Analysis Without a Priori Dimensional Information.

[BibT_eX]

[DOI]

Proceedings of the Independent Component Analysis and Signal Separation, 2007

Undercomplete Blind Subspace Deconvolution Via Linear Prediction.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2007, 2007

2006

ε-Sparse Representations: Generalized Sparse Approximation and the Equivalent Family of SVM Tasks.

[BibT_eX]

[DOI]

Acta Cybern., 2006

Cross-Entropy Optimization for Independent Process Analysis.

[BibT_eX]

[DOI]

Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

2004

L1 regularization is better than L2 for learning and predicting chaotic systems

[BibT_eX]

[DOI]