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Zoltan Szabo
Zoltan Szabo
Professor, LSE
Geverifieerd e-mailadres voor lse.ac.uk - Homepage
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Jaar
Learning Theory for Distribution Regression
Z Szabo, B Sriperumbudur, B Poczos, A Gretton
Journal of Machine Learning Research 17 (152), 1-40, 2016
1962016
Optimal Rates for Random Fourier Features
B Sriperumbudur, Z Szabo
Advances in Neural Information Processing Systems (NIPS), 1144-1152, 2015
1712015
Information theoretical estimators toolbox
Z Szabó
Journal of Machine Learning Research 15 (1), 283-287, 2014
1532014
Interpretable Distribution Features with Maximum Testing Power
W Jitkrittum, Z Szabo, K Chwialkowski, A Gretton
Advances in Neural Information Processing Systems (NIPS), 181-189, 2016
1502016
A Linear-Time Kernel Goodness-of-Fit Test
W Jitkrittum, W Xu, Z Szabo, K Fukumizu, A Gretton
Advances in Neural Information Processing Systems (NIPS), 261-270, 2017
1252017
Two-stage Sampled Learning Theory on Distributions
Z Szabó, A Gretton, B Póczos, B Sriperumbudur
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2015
1062015
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
H Strathmann, D Sejdinovic, S Livingston, Z Szabo, A Gretton
Advances in Neural Information Processing Systems (NIPS), 955-963, 2015
942015
Characteristic and Universal Tensor Product Kernels
Z Szabo, B Sriperumbudur
Journal of Machine Learning Research 18 (233), 1-29, 2018
862018
Online group-structured dictionary learning
Z Szabo, B Poczos, A Lorincz
IEEE Computer Vision and Pattern Recognition (CVPR), 2865-2872, 2011
792011
3D shape estimation in video sequences provides high precision evaluation of facial expressions
L Jeni, A Lorincz, T Nagy, Z Palotai, J Sebok, Z Szabo, D Takacs
Image and Vision Computing, 2012
732012
Undercomplete blind subspace deconvolution
Z Szabó, B Póczos, A Lőrincz
Journal of Machine Learning Research 8, 1063-1095, 2007
642007
Emotional expression classification using time-series kernels
A Lorincz, L Jeni, Z Szabo, J Cohn, T Kanade
IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW …, 2013
612013
Separation theorem for independent subspace analysis and its consequences
Z Szabó, B Póczos, A Lõrincz
Pattern Recognition 45 (4), 1782-1791, 2012
562012
An Adaptive Test of Independence with Analytic Kernel Embeddings
W Jitkrittum, Z Szabo, A Gretton
International Conference on Machine Learning (ICML) 70, 1742-1751, 2017
552017
Spatio-temporal event classification using time-series kernel based structured sparsity
L Jeni, A Lőrincz, Z Szabó, J Cohn, T Kanade
European Conference on Computer Vision (ECCV) 8692, 135-150, 2014
462014
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages
W Jitkrittum, A Gretton, N Heess, A Eslami, B Lakshminarayanan, ...
Conference on Uncertainty in Artificial Intelligence (UAI), 405-414, 2015
442015
MONK – Outlier-Robust Mean Embedding Estimation by Median-of-Means
M Lerasle, Z Szabo, T Mathieu, G Lecue
International Conference on Machine Learning (ICML), 3782-3793, 2019
402019
Cross-entropy optimization for independent process analysis
Z Szabó, B Póczos, A Lőrincz
Independent Component Analysis and Blind Signal Separation (ICA), 909-916, 2006
372006
Bayesian Manifold Learning: The Locally Linear Latent Variable Model
M Park, W Jitkrittum, A Qamar, Z Szabó, L Buesing, M Sahani
Advances in Neural Information Processing Systems (NIPS), 154-162, 2015
30*2015
Hard Shape-Constrained Kernel Machines
PC Aubin-Frankowski, Z Szabo
Advances in Neural Information Processing Systems (NeurIPS), 384-395, 2020
292020
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Artikelen 1–20