Szabo, Zoltan

27 publications

AISTATS 2025 Nyström Kernel Stein Discrepancy Florian Kalinke, Zoltán Szabó, Bharath Sriperumbudur

NeurIPS 2024 The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels Florian Kalinke, Zoltán Szabó

NeurIPS 2023 Kernelized Cumulants: Beyond Kernel Mean Embeddings Patric Bonnier, Harald Oberhauser, Zoltan Szabo

UAI 2023 Nyström $m$-Hilbert-Schmidt Independence Criterion Florian Kalinke, Zoltán Szabó

ICML 2022 Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-Insensitive Losses Alex Lambert, Dimitri Bouche, Zoltan Szabo, Florence D’Alché-Buc

JMLR 2022 Handling Hard Affine SDP Shape Constraints in RKHSs Pierre-Cyril Aubin-Frankowski, Zoltan Szabo

NeurIPS 2020 Hard Shape-Constrained Kernel Machines Pierre-Cyril Aubin-Frankowski, Zoltan Szabo

JMLR 2020 Orlicz Random Fourier Features Linda Chamakh, Emmanuel Gobet, Zoltán Szabó

ICMLW 2019 A Functional Extension of Multi-Output Learning Alex Lambert, Romain Brault, Zoltan Szabo, Florence d'Alche-Buc

AISTATS 2019 Infinite Task Learning in RKHSs Romain Brault, Alex Lambert, Zoltan Szabo, Maxime Sangnier, Florence d’Alche-Buc

ICML 2019 MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means Matthieu Lerasle, Zoltan Szabo, Timothée Mathieu, Guillaume Lecue

AISTATS 2019 On Kernel Derivative Approximation with Random Fourier Features Zoltan Szabo, Bharath Sriperumbudur

NeurIPS 2017 A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton

ICML 2017 An Adaptive Test of Independence with Analytic Kernel Embeddings Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton

NeurIPS 2016 Interpretable Distribution Features with Maximum Testing Power Wittawat Jitkrittum, Zoltán Szabó, Kacper P Chwialkowski, Arthur Gretton

JMLR 2016 Learning Theory for Distribution Regression Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos, Arthur Gretton

NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing, Maneesh Sahani

NeurIPS 2015 Gradient-Free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltan Szabo, Arthur Gretton

UAI 2015 Kernel-Based Just-in-Time Learning for Passing Expectation Propagation Messages Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

NeurIPS 2015 Optimal Rates for Random Fourier Features Bharath Sriperumbudur, Zoltan Szabo

AISTATS 2015 Two-Stage Sampled Learning Theory on Distributions Zoltán Szabó, Arthur Gretton, Barnabás Póczos, Bharath K. Sriperumbudur

MLOSS 2014 Information Theoretical Estimators Toolbox Zoltán Szabó

ECCV 2014 Spatio-Temporal Event Classification Using Time-Series Kernel Based Structured Sparsity László A. Jeni, András Lörincz, Zoltán Szabó, Jeffrey F. Cohn, Takeo Kanade

CVPRW 2013 Emotional Expression Classification Using Time-Series Kernels András Lörincz, László Attila Jeni, Zoltán Szabó, Jeffrey F. Cohn, Takeo Kanade

CVPR 2011 Online Group-Structured Dictionary Learning Zoltán Szabó, Barnabás Póczos, András Lörincz

JMLR 2007 Undercomplete Blind Subspace Deconvolution Zoltán Szabó, Barnabás Póczos, András Lőrincz

IJCAI 1987 Inductive Inference on the Base of Fixed Point Theory Tamás Gergely, Zoltán Szabó