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Handling Hard Affine SDP Shape Constraints in RKHSs


Jan 05, 2021
Pierre-Cyril Aubin-Frankowski, Zoltan Szabo


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Hard Shape-Constrained Kernel Machines


May 26, 2020
Pierre-Cyril Aubin-Frankowski, Zoltan Szabo


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On Kernel Derivative Approximation with Random Fourier Features


Oct 21, 2018
Zoltan Szabo, Bharath K. Sriperumbudur

* Kernel examples fulfilling the Bernstein condition with arbitrary high-order derivatives: included 

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MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means


Oct 17, 2018
Matthieu Lerasle, Zoltan Szabo, Timothee Mathieu, Guillaume Lecue


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Characteristic and Universal Tensor Product Kernels


Aug 02, 2018
Zoltan Szabo, Bharath K. Sriperumbudur

* Journal of Machine Learning Research 18(233):1-29, 2018 
* final version appeared in JMLR 

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A Linear-Time Kernel Goodness-of-Fit Test


Oct 24, 2017
Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton

* Accepted to NIPS 2017 

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Interpretable Distribution Features with Maximum Testing Power


Oct 28, 2016
Wittawat Jitkrittum, Zoltan Szabo, Kacper Chwialkowski, Arthur Gretton


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Learning Theory for Distribution Regression


Oct 21, 2016
Zoltan Szabo, Bharath Sriperumbudur, Barnabas Poczos, Arthur Gretton

* Journal of Machine Learning Research, 17(152):1-40, 2016 
* Final version appeared at JMLR, with supplement. Code: https://bitbucket.org/szzoli/ite/. arXiv admin note: text overlap with arXiv:1402.1754 

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An Adaptive Test of Independence with Analytic Kernel Embeddings


Oct 15, 2016
Wittawat Jitkrittum, Zoltan Szabo, Arthur Gretton

* 8 pages of main text 

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


Dec 01, 2015
Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing, Maneesh Sahani

* accepted to NIPS 2015 

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Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families


Nov 24, 2015
Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltan Szabo, Arthur Gretton

* Advances in Neural Information Processing Systems 28, 2015 
* 20 pages, 7 figures 

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Optimal Rates for Random Fourier Features


Nov 04, 2015
Bharath K. Sriperumbudur, Zoltan Szabo

* To appear at NIPS-2015 

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Two-stage Sampled Learning Theory on Distributions


Jan 26, 2015
Zoltan Szabo, Arthur Gretton, Barnabas Poczos, Bharath Sriperumbudur

* v6: accepted at AISTATS-2015 for oral presentation; final version; code: https://bitbucket.org/szzoli/ite/; extension to the misspecified and vector-valued case: http://arxiv.org/abs/1411.2066 

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Emotional Expression Classification using Time-Series Kernels


Jun 08, 2013
Andras Lorincz, Laszlo Jeni, Zoltan Szabo, Jeffrey Cohn, Takeo Kanade

* IEEE International Workshop on Analysis and Modeling of Faces and Gestures, Portland, Oregon, 28 June 2013 (accepted) 

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Distributed High Dimensional Information Theoretical Image Registration via Random Projections


Oct 02, 2012
Zoltan Szabo, Andras Lorincz

* Zoltan Szabo, Andras Lorincz: Distributed High Dimensional Information Theoretical Image Registration via Random Projections. Digital Signal Processing, 22(6):894-902, 2012 

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Automated Word Puzzle Generation via Topic Dictionaries


Jun 02, 2012
Balazs Pinter, Gyula Voros, Zoltan Szabo, Andras Lorincz

* International Conference on Machine Learning (ICML-2012) - Sparsity, Dictionaries and Projections in Machine Learning and Signal Processing Workshop, Edinburgh, Scotland, 30 June 2012 
* 4 pages 

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Collaborative Filtering via Group-Structured Dictionary Learning


Jan 01, 2012
Zoltan Szabo, Barnabas Poczos, Andras Lorincz

* International Conference on Latent Variable Analysis and Source Separation (LVA/ICA), vol. 7191 of LNCS, pp. 247-254, 2012 
* A compressed version of the paper has been accepted for publication at the 10th International Conference on Latent Variable Analysis and Source Separation (LVA/ICA 2012) 

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Undercomplete Blind Subspace Deconvolution


May 20, 2007
Zoltan Szabo, Barnabas Poczos, Andras Lorincz

* Zoltan Szabo, Barnabas Poczos, Andras Lorincz: Undercomplete Blind Subspace Deconvolution. Journal of Machine Learning Research 8(May):1063-1095, 2007 
* Final version, appeared in Journal of Machine Learning Research 

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