← Authors

Zoltan Szabo

22 papers · 2007–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (18) 🐝 Cross-Pollinator (13) 🗺️ Taxonomy Completionist (32) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 💎 Century Club (22) 🗃️ Keyword Collector (89) 📈 Trend Setter 🔥 Unstoppable (7)

Conferences

NIPS (8) JMLR (6) AISTATS (4) ICML (3) UAI (1)

Top co-authors

Arthur Gretton (6) Wittawat Jitkrittum (4) Bharath Sriperumbudur (4) Barnabás Póczos (3) Florian Kalinke (3) Bharath K. Sriperumbudur (2) Alex Lambert (2) Florence d’Alché-Buc (2) Pierre-Cyril Aubin-Frankowski (2) Maneesh Sahani (1)

Keywords

kernel methods (11) maximum mean discrepancy (6) reproducing kernel hilbert space (5) hilbert-schmidt independence criterion (4) convex optimization (3) statistical test (3) random fourier feature (3) shape constraint (2) distribution regression (2) ridge regression (2) learning theory (2) bayesian inference (2) independence testing (2) quantile regression (2) statistical testing (2) kernel approximation (2) second-order cone programming (2) multi-instance learning (1) statistical learning theory (1) probabilistic modeling (1)

Papers

Nyström Kernel Stein Discrepancy AISTATS 2025
The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels NIPS 2024
Nyström $M$-Hilbert-Schmidt independence criterion UAI 2023
Kernelized Cumulants: Beyond Kernel Mean Embeddings NIPS 2023
Handling Hard Affine SDP Shape Constraints in RKHSs JMLR 2022
Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses ICML 2022
Hard Shape-Constrained Kernel Machines NIPS 2020
Orlicz Random Fourier Features JMLR 2020
On Kernel Derivative Approximation with Random Fourier Features AISTATS 2019
Infinite Task Learning in RKHSs AISTATS 2019
MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means ICML 2019
Characteristic and Universal Tensor Product Kernels JMLR 2018
A Linear-Time Kernel Goodness-of-Fit Test NIPS 2017
An Adaptive Test of Independence with Analytic Kernel Embeddings ICML 2017
Learning Theory for Distribution Regression JMLR 2016
Interpretable Distribution Features with Maximum Testing Power NIPS 2016
Two-stage sampled learning theory on distributions AISTATS 2015
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NIPS 2015
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families NIPS 2015
Optimal Rates for Random Fourier Features NIPS 2015
Information Theoretical Estimators Toolbox JMLR 2014
Undercomplete Blind Subspace Deconvolution JMLR 2007