Adaptive joint distribution learning

10 October 2021

Papers citing "Adaptive joint distribution learning"

11 / 11 papers shown

Title
Toward Large Kernel Models Amirhesam Abedsoltan M. Belkin Parthe Pandit 67 17 0 06 Feb 2023
A Note on Optimizing Distributions using Kernel Mean Embeddings Boris Muzellec Francis R. Bach Alessandro Rudi 18 4 0 18 Jun 2021
A New Parametrization of Correlation Matrices Ilya Archakov P. Hansen 21 41 0 04 Dec 2020
Non-parametric Models for Non-negative Functions Ulysse Marteau-Ferey Francis R. Bach Alessandro Rudi 26 52 0 08 Jul 2020
Kernel methods through the roof: handling billions of points efficiently Giacomo Meanti Luigi Carratino Lorenzo Rosasco Alessandro Rudi 54 115 0 18 Jun 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings Junhyung Park Krikamol Muandet 54 80 0 10 Feb 2020
A Rigorous Theory of Conditional Mean Embeddings I. Klebanov Ingmar Schuster T. Sullivan 43 40 0 02 Dec 2019
Constrained Polynomial Likelihood Caio Almeida Ricardo Masini P. Schneider 59 4 0 30 Oct 2019
Kernel Conditional Density Operators Ingmar Schuster Mattes Mollenhauer Stefan Klus Krikamol Muandet 45 25 0 27 May 2019
Conditional mean embeddings as regressors - supplementary Steffen Grunewalder Guy Lever Luca Baldassarre Sam Patterson Arthur Gretton Massimiliano Pontil 102 144 0 21 May 2012
Estimating divergence functionals and the likelihood ratio by convex risk minimization X. Nguyen Martin J. Wainwright Michael I. Jordan 162 799 0 04 Sep 2008